Publications

Functional annotation

  1. M. Moll, P. W. Finn, and L. E. Kavraki, “Structure-Guided Selection of Specificity Determining Positions in the Human Kinome,” BMC Genomics, vol. 17, no. S4, p. 431, Aug. 2016.
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  2. M. Moll, P. W. Finn, and L. E. Kavraki, “Structure-Guided Selection of Specificity Determining Positions in the Human Kinome,” in 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington, DC, USA, 2015, pp. 21–28.
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  3. J. Chyan, M. Moll, and L. E. Kavraki, “Improving the Prediction of Kinase Binding Affinity Using Homology Models,” in Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics, Wshington DC USA, 2013.
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  4. D. H. Bryant, M. Moll, P. W. Finn, and L. E. Kavraki, “Combinatorial clustering of residue position subsets predicts inhibitor affinity across the human kinome,” PLoS Computational Biology, vol. 9, no. 6, p. e1003087, Jun. 2013.
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  5. M. Moll, D. H. Bryant, and L. E. Kavraki, “The LabelHash Server and Tools for Substructure-Based Functional Annotation,” Bioinformatics, vol. 27, no. 15, pp. 2161–2162, Jun. 2011.
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  6. M. Moll, D. H. Bryant, and L. E. Kavraki, “The LabelHash Algorithm for Substructure Matching,” BMC Bioinformatics, vol. 11, no. 1, p. 555, Nov. 2010.
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  7. D. H. Bryant, M. Moll, B. Y. Chen, V. Y. Fofanov, and L. E. Kavraki, “Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction,” BMC Bioinformatics, vol. 11, no. 1, p. 242, May 2010.
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  8. V. Y. Fofanov, B. Y. Chen, D. H. Bryant, M. Moll, O. Lichtarge, L. E. Kavraki, and M. Kimmel, “A Statistical Model to Correct Systematic Bias Introduced by Algorithmic Thresholds in Protein Structural Comparison Algorithms,” in 2008 IEEE International Conference on Bioinformatics and Biomeidcine Workshops, Philadelphia, PA, 2008.
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  9. M. Moll and L. E. Kavraki, “Matching of Structural Motifs Using Hashing on Residue Labels and Geometric Filtering for Protein Function Prediction,” in Computational Systems Bioinformatics, Stanford University, USA, 2008, pp. 157–168.
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  10. M. Moll and L. E. Kavraki, “LabelHash: A Flexible and Extensible Method for Matching Structural Motifs,” in Nature Precedings, 2008.
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  11. D. M. Kristensen, M. R. Ward, A. M. Lisewski, S. Edrin, B. Y. Chen, V. Y. Fofanov, M. Kimmel, L. E. Kavraki, and O. Lichtarge, “Prediction of enzyme function based on 3D templates of evolutionarily important amino acids,” BMC Bioinformatics, vol. 9, no. 1, Jan. 2008.
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  12. B. Y. Chen, D. H. Bryant, A. E. Cruess, J. H. Bylund, V. Y. Fofanov, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Composite Motifs Integrating Multiple Protein Structures Increase Sensitivity for Function Prediction,” in Computational Systems Bioinformatics, University of California, San Diego, USA, 2007, pp. 343–355.
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  13. B. Y. Chen, V. Y. Fofanov, D. H. Bryant, B. D. Dodson, D. M. Kristensen, A. M. Lisewski, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “The MASH Pipeline for Protein Function Prediction and an Algorithm for the Geometric Refinement of 3D Motifs,” Journal of Computational Biology, vol. 14, no. 6, pp. 791–816, Jul. 2007.
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  14. B. Y. Chen, D. H. Bryant, V. Y. Fofanov, D. M. Kristensen, A. E. Cruess, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Cavity Scaling: Automated Refinement of Cavity-Aware Motifs in Protein Function Prediction,” Journal of Bioinformatics and Computational Biology, vol. 05, no. 02a, pp. 353–382, Apr. 2007.
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  15. A. Shehu, C. Clementi, and L. E. Kavraki, “Modeling Protein Conformational Ensembles: From Missing Loops to Equilibrium Fluctuations,” Proteins: Structure, Function, and Bioinformatics, vol. 65, no. 1, pp. 164–179, Aug. 2006.
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  16. B. Y. Chen, D. H. Bryant, V. Y. Fofanov, D. M. Kristensen, A. E. Cruess, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Cavity-Aware Motifs Reduce False Positives in Protein Function Prediction,” in Computational Systems Bioinformatics, Stanford CA, 2006, vol. 4, pp. 311–323.
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  17. D. M. Kristensen, B. Y. Chen, V. Y. Fofanov, M. R. Ward, A. M. Lisewski, M. Kimmel, L. E. Kavraki, and O. Lichtarge, “Recurrent Use of Evolutionary Importance for Functional Annotation of Proteins Based on Local Structural Similarity,” Protein Science, vol. 15, no. 6, pp. 1530–1536, Jun. 2006.
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  18. B. Y. Chen, V. Y. Fofanov, D. H. Bryant, B. D. Dodson, D. M. Kristensen, A. M. Lisewski, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Geometric Sieving: Automated Distributed Optimization of 3D Motifs for Protein Function Prediction,” in Lecture Notes in Computer Science, Venice, Italy, 2006, pp. 500–515.
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  19. B. Y. Chen, V. Y. Fofanov, D. M. Kristensen, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Algorithms for Structural Comparison and Statistical Analysis of 3D Protein Motifs,” in Biocomputing 2005, Hawaii, USA, 2004.
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  20. M. Zhang, R. A. White, L. Wang, R. Goldman, L. E. Kavraki, and B. Hassett, “Improving Conformational Searches by Geometric Screening,” Bioinformatics, vol. 21, no. 5, pp. 624–630, Oct. 2004.
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  21. H. Yao, D. M. Kristensen, I. Mihalek, M. Sowa, C. Shaw, M. Kimmel, L. E. Kavraki, and O. Lichtarge, “An Accurate, Sensitive, and Scalable Method to Identify Functional Sites in Protein Structures,” Journal of Molecular Biology, vol. 326, no. 1, pp. 255–261, Feb. 2003.
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Fundamentals of protein modeling

  1. D. A. Antunes, J. R. Abella, S. Hall-Swan, D. Devaurs, A. Conev, M. Moll, G. Lizée, and L. E. Kavraki, “HLA-Arena: a customizable environment for the structural modeling and analysis of peptide-HLA complexes for cancer immunotherapy,” JCO Clinical Cancer Informatics, vol. 4, no. 4, pp. 623–636, Sep. 2020.
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  2. J. R. Abella, D. A. Antunes, C. Clementi, and L. E. Kavraki, “Large-scale structure-based prediction of stable peptide binding to Class I HLAs using random forests,” Frontiers in Immunology, vol. 11, no. 1583, Jul. 2020.
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  3. J. R. Abella, D. A. Antunes, C. Clementi, and L. E. Kavraki, “APE-Gen: A Fast Method for Generating Ensembles of Bound Peptide-MHC Conformations,” Molecules, vol. 24, no. 5, p. 881, Mar. 2019.
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  4. E. Hruska, J. R. Abella, F. Nüske, L. E. Kavraki, and C. Clementi, “Quantitative comparison of adaptive sampling methods for protein dynamics,” The Journal of Chemical Physics, vol. 149, no. 24, p. 244119, Dec. 2018.
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  5. D. Devaurs, D. A. Antunes, and L. E. Kavraki, “Revealing Unknown Protein Structures Using Computational Conformational Sampling Guided by Experimental Hydrogen-Exchange Data,” International Journal of Molecular Sciences, vol. 19, no. 11, p. 3406, Oct. 2018.
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  6. J. R. Abella, M. Moll, and L. E. Kavraki, “Maintaining and Enhancing Diversity of Sampled Protein Conformations in Robotics-Inspired Methods,” Journal of Computational Biology, vol. 25, no. 1, pp. 3–20, Jan. 2018.
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  7. D. Devaurs, M. Papanastasiou, D. A. Antunes, J. R. Abella, M. Moll, D. Ricklin, J. D. Lambris, and L. E. Kavraki, “Native state of complement protein C3d analysed via hydrogen exchange and conformational sampling,” International Journal of Computational Biology and Drug Design, vol. 11, no. 1/2, p. 90, 2018.
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  8. D. Devaurs, D. A. Antunes, M. Papanastasiou, M. Moll, D. Ricklin, J. D. Lambris, and L. E. Kavraki, “Coarse-grained conformational sampling of protein structure improves the fit to experimental hydrogen-exchange data,” Frontiers in Molecular Biosciences, vol. 4, no. 13, Mar. 2017.
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  9. A. Novinskaya, D. Devaurs, M. Moll, and L. E. Kavraki, “Defining low-dimensional projections to guide protein conformational sampling,” Journal of Computational Biology, vol. 24, no. 1, pp. 79–89, Jan. 2017.
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  10. A. Novinskaya, D. Devaurs, M. Moll, and L. E. Kavraki, “Improving protein conformational sampling by using guiding projections,” in 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington, DC, USA, 2015, pp. 1272–1279.
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  11. B. Gipson, D. Hsu, L. E. Kavraki, and J.-C. Latombe, “Computational Models of Proteins Kinematics and Dynamics: Beyond Simulation,” Annual Reviews of Analytical Chemistry, vol. 5, pp. 273–291, Apr. 2012.
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  12. A. Shehu and L. E. Kavraki, “Modeling Structures and Motions of Loops in Protein Molecules,” Entropy, vol. 14, no. 2, pp. 252–290, Feb. 2012.
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  13. N. Haspel, M. Moll, M. L. Baker, W. Chiu, and L. E. Kavraki, “Tracing conformational changes in proteins,” BMC Structural Biology, vol. 10, no. Suppl 1, p. S1, 2010.
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  14. A. P. Heath, L. E. Kavraki, and C. Clementi, “From coarse-grain to all-atom: Toward multiscale analysis of protein landscapes,” Proteins: Structure, Function, and Bioinformatics, vol. 68, no. 3, pp. 646–661, May 2007.
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  15. B. Y. Chen, D. H. Bryant, V. Y. Fofanov, D. M. Kristensen, A. E. Cruess, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Cavity-Aware Motifs Reduce False Positives in Protein Function Prediction,” in Computational Systems Bioinformatics, Stanford CA, 2006, vol. 4, pp. 311–323.
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  16. P. Das, M. Moll, H. Stamati, L. E. Kavraki, and C. Clementi, “Low-dimensional Free-energy Landscapes of Protein-Folding Reactions by Nonlinear Dimensionality Reduction,” Proceedings of the National Academy of Sciences, vol. 103, no. 26, pp. 9885–9890, Jun. 2006.
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  17. B. Y. Chen, V. Y. Fofanov, D. H. Bryant, B. D. Dodson, D. M. Kristensen, A. M. Lisewski, M. Kimmel, O. Lichtarge, and L. E. Kavraki, “Geometric Sieving: Automated Distributed Optimization of 3D Motifs for Protein Function Prediction,” in Lecture Notes in Computer Science, Venice, Italy, 2006, pp. 500–515.
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  18. M. Zhang and L. E. Kavraki, “Approximating Solutions of Molecular Inverse Kinematics Problems by Subdivision,” in Proceedings of the Second Joint 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society] [Engineering in Medicine and Biology, Houston, TX, USA, 2002, pp. 2182–2183.
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  19. M. Zhang and L. E. Kavraki, “Solving Molecular Inverse Kinematics Problems for Protein Folding and Drug Design,” in Currents in Computational Molecular Biology, 2002, pp. 214–215.
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  20. M. Zhang and L. E. Kavraki, “A New Method for Fast and Accurate Derivation of Molecular Conformations,” Journal of Chemical Information and Computer Sciences, vol. 42, no. 1, pp. 64–70, Dec. 2001.
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  21. M. Zhang and L. E. Kavraki, “Efficiently Maintaining Molecular Conformations Using Local Frames,” in Currents in Computational Molecular Biology, Montreal, Canada, 2001, pp. 97–98.
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Fundamentals of sampling-based motion planning

  1. Z. Kingston, C. Chamzas, and L. E. Kavraki, “Using Experience to Improve Constrained Planning on Foliations for Multi-Modal Problems,” in 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Prague, Czech Republic, 2021.
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  2. C. Quintero-Peña, C. Chamzas, V. Unhelkar, and L. E. Kavraki, “Motion Planning via Bayesian Learning in the Dark,” in ICRA 2021: Workshop on Machine Learning for Motion Planning, 2021.
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  3. C. Chamzas, Z. Kingston, C. Quintero-Peña, A. Shrivastava, and L. E. Kavraki, “Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions,” in 2021 IEEE International Conference on Robotics and Automation (ICRA), Xi’an, China, 2021, pp. 1283–1289. (Top-4 finalist for best paper in Cognitive Robotics)
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  4. Z. Kingston, A. M. Wells, M. Moll, and L. E. Kavraki, “Informing Multi-Modal Planning with Synergistic Discrete Leads,” in 2020 IEEE International Conference on Robotics and Automation (ICRA), Paris, France, 2020, pp. 3199–3205.
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  5. K. E. Bekris, B. Y. Chen, A. M. Ladd, E. Plaku, and L. E. Kavraki, “Multiple Query Probabilistic Roadmap Planning Using Single Query Planning Primitives,” in Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453), Las Vegas, NV, USA, 2020, pp. 656–661.
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  6. Z. Kingston, M. Moll, and L. E. Kavraki, “Decoupling Constraints from Sampling-Based Planners,” in Springer Proceedings in Advanced Robotics, Puerto Varas, Chile, 2019, pp. 913–928.
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  7. Z. Kingston, M. Moll, and L. E. Kavraki, “Exploring Implicit Spaces for Constrained Sampling-Based Planning,” The International Journal of Robotics Research, vol. 38, no. 10–11, pp. 1151–1178, Aug. 2019.
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  8. C. Chamzas, A. Shrivastava, and L. E. Kavraki, “Using Local Experiences for Global Motion Planning,” in 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 8606–8612.
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  9. Z. K. Kingston, M. Moll, and L. E. Kavraki, “Sampling-Based Methods for Motion Planning with Constraints,” Annual Review of Control, Robotics, and Autonomous Systems, vol. 1, no. 1, pp. 159–185, May 2018.
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  10. S. M. LaValle, J. Yakey, and L. E. Kavraki, “A Probabilistic Roadmap Approach for Systems with Closed Kinematic Chains,” in Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C), Detroit, MI, USA, 2017, vol. 3, pp. 1671–1677.
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  11. L. E. Kavraki, M. N. Kolountzakis, and J.-C. Latombe, “Analysis of Probabilistic Roadmaps for Path Planning,” in Proceedings of IEEE International Conference on Robotics and Automation, Minneapolis, MN, USA, 2017, pp. 3020–3026.
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  12. L. E. Kavraki and J.-C. Latombe, “Randomized Preprocessing of Configuration Space for Path Planning: Articulated Robots,” in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS’94), Munich, Germany, 2017, pp. 1764–1771.
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  13. D. Halperin, L. E. Kavraki, and K. Solovey, “Robotics,” in Handbook of Discrete and Computational Geometry, J. E. Goodman, J. O’Rourke, and C. D. Tóth, Eds. Boca Raton, NY: CRC Press, 2017.
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  14. F. T. Pokorny, D. Kragic, L. E. Kavraki, and K. Goldberg, “High-Dimensional Winding-Augmented Motion Planning with 2D Topological Task Projections and Persistent Homology,” in 2016 IEEE International Conference on Robotics and Automation (ICRA), Stockholm, Sweden, 2016, pp. 24–31.
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  15. L. E. Kavraki and S. M. LaValle, “Motion Planning,” in Handbook of Robotics, 2nd Edition, Springer, 2016.
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  16. B. Gipson, M. Moll, and L. E. Kavraki, “Resolution Independent Density Estimation for Motion Planning in High-Dimensional Spaces,” in 2013 IEEE International Conference on Robotics and Automation, Karlsruhe, Germany, 2013, pp. 2429–2435.
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  17. I. A. Sucan and L. E. Kavraki, “A Sampling-Based Tree Planner for Systems With Complex Dynamics,” IEEE Transactions on Robotics, vol. 28, no. 1, pp. 116–131, Feb. 2012.
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  18. I. A. Sucan and L. E. Kavraki, “On the Implementation of Single-Query Sampling-Based Motion Planners,” in 2010 IEEE International Conference on Robotics and Automation, Anchorage, AK, 2010, pp. 2005–2011.
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  19. I. A. Sucan and L. E. Kavraki, “On the Performance of Random Linear Projections for Sampling-Based Motion Planning,” in 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, 2009, pp. 2434–2439.
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  20. K. I. Tsianos, D. Halperin, L. E. Kavraki, and J.-C. Latombe, “Robot Algorithms,” in Algorithms and Theory of Computation Handbook, Second., vol. 2, Boca Raton, FL: CRC Press, 2008.
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  21. K. I. Tsianos, I. A. Sucan, and L. E. Kavraki, “Sampling-based robot motion planning: Towards realistic applications,” Computer Science Review, vol. 1, no. 1, pp. 2–11, Aug. 2007.
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  22. E. Plaku and L. E. Kavraki, “Nonlinear Dimensionality Reduction Using Approximate Nearest Neighbors,” in Proceedings of the 2007 SIAM International Conference on Data Mining, Minneapolis, Minnesota, 2007, pp. 3711–3716.
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  23. M. Moll and L. E. Kavraki, “Path Planning for Deformable Linear Objects,” IEEE Transactions on Robotics, vol. 22, no. 4, pp. 625–636, Aug. 2006.
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  24. E. Plaku and L. E. Kavraki, “Quantitative Analysis of Nearest Neighbors Search in High-Dimensional Sampling-based Motion Planning,” in Workshop on Algorithmic Foundations of Robotics (WAFR), New York, NY, 2006.
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  25. K. E. Bekris, A. A. Argyros, and L. E. Kavraki, “Exploiting Panoramic Vision for Angle-Based Robot Navigation,” in Lecture Notes in Computer Science, Vol. 33, Springer, 2006, pp. 229–251.
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  26. E. Plaku, K. E. Bekris, B. Y. Chen, A. M. Ladd, and L. E. Kavraki, “Sampling-Based Roadmap of Trees for Parallel Motion Planning,” IEEE Transactions on Robotics, vol. 21, no. 4, pp. 597–608, Aug. 2005.
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  27. H. Choset, W. Burgard, S. Hutchinson, G. Kantor, L. E. Kavraki, K. Lynch, and S. Thrun, Principles of Robot Motion: Theory, Algorithms, and Implementation. MIT Press, 2005.
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  28. E. Plaku and L. E. Kavraki, “Distributed Sampling-Based Roadmap of Trees for Large-Scale Motion Planning,” in Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, 2005, pp. 3879–3884.
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  29. A. M. Ladd and L. E. Kavraki, “Fast Tree-Based Exploration of State Space for Robots with Dynamics,” in Algorithmic Foundations of Robotics VI, Springer, STAR 17, 2005, pp. 297–312.
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  30. M. Akinc, K. E. Bekris, B. Y. Chen, A. M. Ladd, E. Plaku, and L. E. Kavraki, “Probabilistic Roadmaps of Trees for Parallel Computation of Multiple Query Roadmaps,” in Robotic Research: The Eleventh International Symposium, Springer, STAR 15, 2005, pp. 80–89.
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  31. A. M. Ladd and L. E. Kavraki, “Measure Theoretic Analysis of Probabilistic Path Planning,” IEEE Transactions on Robotics and Automation, vol. 20, no. 2, pp. 229–242, Apr. 2004.
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  32. D. Halperin, L. E. Kavraki, and J.-C. Latombe, “Robotics,” in Handbook of Discrete and Computational Geometry, Boca Raton, NY: CRC Press, 2004, pp. 1065–1094.
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  33. P. K. Agrawal, L. J. Guibas, H. Edelsbrunner, J. Erickson, M. Isard, S. Har-Peled, J. Hershberger, C. Jensen, L. E. Kavraki, P. Koehl, M. Lin, D. Manocha, D. Metaxas, B. Mirtich, D. Mount, and S. Muthukrishnan, “Algorithmic Issues in Modeling Motion,” ACM Computing Surveys, vol. 34, no. 4, pp. 550–572, Dec. 2002.
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  34. A. M. Ladd and L. E. Kavraki, “Generalizing the Analysis of PRM,” in Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), Washington, DC, USA, 2002, pp. 2120–2125.
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  35. O. Brock and L. E. Kavraki, “Decomposition-Based Motion Planning: A Framework for Real-Time Motion Planning in High-Dimensional Configuration Places,” in Proceedings of The 2001 IEEE International Conference on Robotics and Automation (ICRA), 2001, pp. 1469–1475.
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  36. J. Yakey, S. M. LaValle, and L. E. Kavraki, “Randomized Path Planning for Linkages with Closed Kinematics Chains,” IEEE Transactions on Robotics and Automation, vol. 17, no. 6, pp. 951–959, 2001.
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  37. R. Bohlin and L. E. Kavraki, “A Randomized Algorithm for Robot Path Planning Based on Lazy Evaluation,” in Handbook on Randomized Computing, Kluwer Academic Publishers, 2001, pp. 221–249.
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  38. C. Nielsen and L. E. Kavraki, “A Two-Level Fuzzy PRM for Manipulation Planning,” in Proceedings of The IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2000, vol. 3, pp. 1716–1722.
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  39. T. Danner and L. E. Kavraki, “Randomized Planning for Short Inspection Paths,” in Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), San Francisco, CA, USA, 2000, vol. 2, pp. 971–976.
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  40. R. Bohlin and L. E. Kavraki, “Path Planning Using Lazy PRM,” in Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), San Francisco, CA, USA, 2000, vol. 1, pp. 521–528.
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  41. C. Holleman and L. E. Kavraki, “A Framework for Using the Workspace Medial Axis in PRM Planners,” in Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), San Francisco, CA, USA, 2000, vol. 2, pp. 1408–1413.
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  42. L. E. Kavraki, “Algorithms in Robotics: The Motion Planning Perspective,” in Frontiers of Engineering Publication, National Academy of Engineering, 1999, pp. 90–93.
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  43. D. Hsu, J.-C. Latombe, R. Motwani, and L. E. Kavraki, “Capturing the Connectivity of High-Dimensional Geometric Spaces by Parallelizable Random Sampling Techniques,” in Parallel and Distributed Processing, vol. 5, P. M. Pardalos and S. Rajasekaran, Eds. Springer, Boston, MA., 1999, pp. 159–182.
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  44. D. Halperin, L. E. Kavraki, J.-C. Latombe, and M. Attalah, “Robot Algorithms,” in Algorithms and Theory of Computation Handbook, Boca Raton, NY: CRC Press, 1999.
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  45. L. J. Guibas, C. Holleman, and L. E. Kavraki, “A Probabilistic Roadmap Planner for Flexible Objects with a Workspace Medial-Axis Based Sampling Approach,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Kyongju, Korea, 1999, vol. 1, pp. 254–260.
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  46. L. E. Kavraki, J.-C. Latombe, R. Motwani, and P. Raghavan, “Randomized Query Processing in Robot Path Planning,” Journal of Computer and System Sciences, vol. 57, no. 1, pp. 50–60, Aug. 1998.
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  47. L. E. Kavraki, M. N. Kolountzakis, and J.-C. Latombe, “Analysis of Probabilistic Roadmaps for Path Planning,” IEEE Transactions on Robotics and Automation, vol. 14, no. 1, pp. 166–171, Feb. 1998.
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  48. L. E. Kavraki and J.-C. Latombe, “Probabilistic Roadmaps for Robot Path Planning,” in Practical Motion Planning in Robotics: Current Approaches and Future Directions, John Wiley, 1998, pp. 33–53.
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  49. D. Hsu, L. E. Kavraki, J.-C. Latombe, R. Motwani, and S. Sorkin, “On Finding Narrow Passages with Probabilistic Roadmap Planners,” in Robotics: The algorithmic perspective, Natick, MA: A.K. Peters, 1998, pp. 141–153.
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  50. P. K. Agrawal, L. E. Kavraki, and M. Mason, Robotics: The Algorithmic Perspective. Natick MA: A.K. Peters, 1998.
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  51. B. Barraquand, L. E. Kavraki, J.-C. Latombe, T.-Y. Li, R. Motwani, and P. Raghavan, “A Random Sampling Scheme for Robot Path Planning,” International Journal of Robotics Research, vol. 16, no. 6, pp. 759–774, 1997.
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  52. L. E. Kavraki, P. Švestka, J.-C. Latombe, and M. Overmars, “Probabilistic Roadmaps for Path Planning in High Dimensional Configuration Spaces,” IEEE Transactions on Robotics and Automation, vol. 12, no. 4, pp. 566–580, 1996.
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  53. B. Barraquand, L. E. Kavraki, J.-C. Latombe, T.-Y. Li, R. Motwani, and P. Raghavan, “A Random Sampling Scheme for Robot Path Planning,” in Robotics Research, North Holland, 1996, pp. 249–264.
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  54. L. E. Kavraki, J.-C. Latombe, R. Motwani, and P. Raghavan, “Randomized Query Processing in Robot Path Planning,” in Proceedings of the twenty-seventh annual ACM symposium on Theory of computing - STOC ’95, Las Vegas, Nevada, United States, 1995, pp. 353–362.
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  55. L. E. Kavraki and J.-C. Latombe, “Randomized Preprocessing of Configuration Space for Fast Path Planning,” in Proceedings of the International Conference on Robotics and Automation (ICRA), San Diego, CA, 1994, pp. 2138–2139.
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Kinodynamic systems

  1. S. Butler, M. Moll, and L. E. Kavraki, “A General Algorithm for Time-Optimal Trajectory Generation Subject to Minimum and Maximum Constraints,” in Springer Proceedings in Advanced Robotics, 2020, pp. 368–383.
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  2. E. Vidal Garcia, M. Moll, N. Palomeras, J. D. Hernández, M. Carreras, and L. E. Kavraki, “Online Multilayered Motion Planning with Dynamic Constraints for Autonomous Underwater Vehicles,” in 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 8936–8942. (Top-3 finalist for best student paper award)
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  3. Muhayyuddin, M. Moll, L. E. Kavraki, and J. Rosell, “Randomized Physics-based Motion Planning for Grasping in Cluttered and Uncertain Environments,” IEEE Robotics and Automation Letters, vol. 3, no. 2, pp. 712–719, Apr. 2018.
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  4. B. Gipson, D. Hsu, L. E. Kavraki, and J.-C. Latombe, “Computational Models of Proteins Kinematics and Dynamics: Beyond Simulation,” Annual Reviews of Analytical Chemistry, vol. 5, pp. 273–291, Apr. 2012.
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  5. K. E. Bekris, D. K. Grady, M. Moll, and L. E. Kavraki, “Safe Distributed Motion Coordination for Second-Order Systems With Different Planning Cycles,” The International Journal of Robotics Research, vol. 31, no. 2, pp. 129–150, Feb. 2012.
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  6. D. K. Grady, K. E. Bekris, and L. E. Kavraki, “Asynchronous Distributed Motion Planning with Safety Guarantees under Second-Order Dynamics,” in Algorithmic Foundations of Robotics IX, vol. 68, Singapore, Singapore: Springer Berlin / Heidelberg, 2011, pp. 53–70.
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  7. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Motion Planning with Dynamics by a Synergistic Combination of Layers of Planning,” IEEE Transactions on Robotics, vol. 26, no. 3, pp. 469–482, Jun. 2010.
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  8. K. E. Bekris, K. I. Tsianos, and L. E. Kavraki, “Safe and Distributed Kinodynamic Replanning for Vehicular networks,” Mobile Networks and Applications, vol. 14, no. 3, pp. 292–308, Feb. 2009.
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  9. I. A. Sucan and L. E. Kavraki, “Kinodynamic Motion Planning by Interior-Exterior Cell Exploration,” in Springer Tracts in Advanced Robotics, Guanajuato, Mexico, 2009, vol. 57, pp. 449–464.
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  10. K. I. Tsianos and L. E. Kavraki, “Replanning: A powerful planning strategy for hard kinodynamic problems,” in 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Nice, 2008, pp. 1667–1672.
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  11. I. A. Sucan, J. F. Kruse, M. Yim, and L. E. Kavraki, “Kinodynamic Motion Planning with Hardware Demonstrations,” in 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, Nice, 2008, pp. 1661–1666.
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  12. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Discrete Search Leading Continuous Exploration for Kinodynamic Motion Planning,” in Robotics, Atlanta, Georgia, 2008, pp. 326–333.
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  13. I. A. Sucan, J. F. Kruse, M. Yim, and L. E. Kavraki, “Reconfiguration for modular robots using kinodynamic motion planning,” in ASME 2008 Dynamic Systems and Control Conference, Parts A and B, Ann Arbor, Michigan, USA, 2008.
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  14. K. E. Bekris, K. I. Tsianos, and L. E. Kavraki, “A Distributed Protocol for Safe Real-Time Planning of Communicating Vehicles with Second-Order Dynamics,” in The Proceedings of First International Conference on Robot Communication and Coordination, Athens, Greece, 2007.
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  15. K. E. Bekris, K. I. Tsianos, and L. E. Kavraki, “A Decentralized Planner that Guarantees the Safety of Communicating Vehicles with Complex Dynamics that Replan Online,” in 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, 2007.
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  16. K. E. Bekris and L. E. Kavraki, “Greedy but Safe Replanning under Kinodynamic Constraints,” in Proceedings 2007 IEEE International Conference on Robotics and Automation, Rome, Italy, 2007, pp. 704–710.
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  17. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “A Motion Planner for a Hybrid Robotic System with Kinodynamic Constraints,” in Proceedings 2007 IEEE International Conference on Robotics and Automation, Roma, 2007, pp. 692–697.
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  18. A. M. Ladd and L. E. Kavraki, “Motion Planning in the Presence of Drift, Underactuation and Discrete System Changes,” in Robotics: Science and Systems I, Boston, MA, 2005, pp. 233–241.
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  19. A. M. Ladd and L. E. Kavraki, “Fast Tree-Based Exploration of State Space for Robots with Dynamics,” in Algorithmic Foundations of Robotics VI, Springer, STAR 17, 2005, pp. 297–312.
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  20. J. M. Phillips, N. Bedrosian, and L. E. Kavraki, “Guided Expansive Spaces Trees: A Search Strategy for Motion- and Cost-Constrained State Spaces,” in IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA ’04. 2004, New Orleans, LA, USA, 2004, pp. 3968–3973.
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  21. J. M. Phillips, L. E. Kavraki, and N. Bedrosian, “Spacecraft Rendezvous and Docking With Real-Time Randomized Optimization,” in AIAA (American Institute of Aeronautics and Astronautics) Guidance, Navigation and Control Conference, Austin, TX, 2003.
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  22. J. M. Phillips, L. E. Kavraki, and N. Bedrosian, “Probabilistic Optimization Applied to Spacecraft Rendezvous and Docking,” in 13th American Astronomical Society/AIAA - Space Flight Mechanics Meeting, Puerto Rico, 2003.
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Localization

  1. A. M. Ladd, K. E. Bekris, G. Marceau, A. Rudys, L. E. Kavraki, and D. S. Wallach, “Using Wireless Ethernet for Localization,” in IEEE/RSJ International Conference on Intelligent Robots and System, Lausanne, Switzerland, 2020, vol. 1, pp. 402–408.
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  2. K. E. Bekris, M. Glick, and L. E. Kavraki, “Evaluation of Algorithms for Bearing-Only SLAM,” in Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006., Orlando, FL, 2006, pp. 1937–1944.
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  3. A. M. Ladd, K. E. Bekris, A. Rudys, G. Marceau, L. E. Kavraki, and D. S. Wallach, “Robotics-Based Location Sensing using Wireless Ethernet,” Wireless Networks (The Journal of Mobile Communication, Computation and Information), vol. 11, no. 1-2, pp. 189–204, Jan. 2005.
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  4. A. Haeberlen, E. Flannery, A. M. Ladd, A. Rudys, D. S. Wallach, and L. E. Kavraki, “Practical Robust Localization over Large-Scale 802.11 Wireless Networks,” in Proceedings of the 10th annual international conference on Mobile computing and networking - MobiCom ’04, Philadelphia, PA, USA, 2004, pp. 70–84.
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  5. A. M. Ladd, K. E. Bekris, A. Rudys, L. E. Kavraki, and D. S. Wallach, “On the Feasibility of Using Wireless Ethernet for Indoor Localization,” IEEE Transactions on Robotics and Automation, vol. 20, no. 3, pp. 555–559, Jun. 2004.
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  6. A. M. Ladd, K. E. Bekris, A. Rudys, G. Marceau, L. E. Kavraki, and D. S. Wallach, “Robotics-Based Location Sensing using Wireless Ethernet,” in Proceedings of the 8th annual international conference on Mobile computing and networking - MobiCom ’02, Atlanta, Georgia, USA, 2002, pp. 227–238.
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Metabolic networks

  1. E. E. Litsa, M. I. Pena, M. Moll, G. Giannakopoulos, G. N. Bennett, and L. E. Kavraki, “Machine Learning Guided Atom Mapping of Metabolic Reactions,” Journal of Chemical Information and Modeling, vol. 59, no. 3, pp. 1121–1135, Nov. 2018.
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  2. S. M. Kim, M. I. Peña, M. Moll, G. N. Bennett, and L. E. Kavraki, “A Review of Parameters and Heuristics for Guiding Metabolic Pathfinding,” Journal of Cheminformatics, vol. 9, no. 1, p. 51, Sep. 2017.
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  3. S. M. Kim, M. I. Peña, M. Moll, G. Giannakopoulos, G. N. Bennett, and L. E. Kavraki, “An Evaluation of Different Clustering Methods and Distance Measures Used for Grouping Metabolic Pathways,” in 2016 International Conference on Bioinformatics and Computational Biology. ISCA, 2016, pp. 115–122.
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  4. A. P. Heath, G. N. Bennett, and L. E. Kavraki, “An Algorithm for Efficient Identification of Branched Metabolic Pathways,” Journal of Computational Biology, vol. 18, no. 11, pp. 1575–1597, Nov. 2011.
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  5. A. P. Heath, G. N. Bennett, and L. E. Kavraki, “Identifying Branched Metabolic Pathways by Merging Linear Metabolic Pathways,” Lecture Notes in Computer Science, vol. 6577/2011, pp. 70–84, 2011.
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  6. A. P. Heath, G. N. Bennett, and L. E. Kavraki, “Finding Metabolic Pathways Using Atom Tracking,” Bioinformatics, vol. 26, no. 12, pp. 1548–1555, Apr. 2010.
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Other biomedical computing

  1. D. A. Antunes, J. R. Abella, S. Hall-Swan, D. Devaurs, A. Conev, M. Moll, G. Lizée, and L. E. Kavraki, “HLA-Arena: a customizable environment for the structural modeling and analysis of peptide-HLA complexes for cancer immunotherapy,” JCO Clinical Cancer Informatics, vol. 4, no. 4, pp. 623–636, Sep. 2020.
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  2. J. R. Abella, D. A. Antunes, C. Clementi, and L. E. Kavraki, “Large-scale structure-based prediction of stable peptide binding to Class I HLAs using random forests,” Frontiers in Immunology, vol. 11, no. 1583, Jul. 2020.
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  3. D. A. Antunes, M. Moll, D. Devaurs, K. R. Jackson, G. Lizée, and L. E. Kavraki, “DINC 2.0: a new protein-peptide docking webserver using an incremental approach,” Cancer Research, vol. 77, no. 21, pp. e55–57, Nov. 2017.
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  4. A. Schweikard, R. Tombropoulos, L. E. Kavraki, J. Adler, and J.-C. Latombe, “Treatment Planning for a Radiosurgical System with General Kinematics,” in Proceedings of the 1994 IEEE International Conference on Robotics and Automation, San Diego, CA, USA, 2017, pp. 1764–1771.
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  5. A. P. Heath and L. E. Kavraki, “Computational Challenges in Systems Biology,” Computer Science Review, vol. 3, no. 1, pp. 1–17, Feb. 2009.
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  6. A. P. Heath, G. Balázsi, and L. E. Kavraki, “Bipolarity of the saccharomyces cerevisiae genome,” 2008 2nd International Conference on Bioinformatics and Biomedical Engineering, pp. 330–333, May 2008.
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  7. M. L. Teodoro and L. E. Kavraki, “Pharmacology,” in Handbook of Data Mining and Knowledge Discovery, W. Klösgen and J. Żytkow, Eds. Oxford University Press, 2002, pp. 808–816.
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Other robotics

  1. C. Chamzas, M. Lippi, M. C. Welle, A. Varava, A. Marino, L. E. Kavraki, and D. Kragic, “State Representations in Robotics: Identifying Relevant Factors of Variation using Weak Supervision,” in NeurIPS, 3rd Robot Learning Workshop: Grounding Machine Learning Development in the Real World, 2020.
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  2. J. D. Hernández, E. Vidal, M. Moll, N. Palomeras, M. Carreras, and L. E. Kavraki, “Online Motion Planning for Unexplored Underwater Environments using Autonomous Underwater Vehicles,” Journal of Field Robotics, vol. 36, no. 2, pp. 370–396, Nov. 2018.
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  3. J. Luo and L. E. Kavraki, “Part Assembly Using Static and Dynamic Force Fields,” in Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113), Takamatsu, Japan, 2017, vol. 2, pp. 1468–1474.
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  4. C. Holleman, L. E. Kavraki, and J. Warren, “Planning Paths for a Flexible Surface Patch,” in Proceedings. 1998 IEEE International Conference on Robotics and Automation (Cat. No.98CH36146), Leuven, Belgium, 2017, vol. 1, pp. 21–26.
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  5. A. Schweikard, R. Tombropoulos, L. E. Kavraki, J. Adler, and J.-C. Latombe, “Treatment Planning for a Radiosurgical System with General Kinematics,” in Proceedings of the 1994 IEEE International Conference on Robotics and Automation, San Diego, CA, USA, 2017, pp. 1764–1771.
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  6. J. M. Phillips, A. M. Ladd, and L. E. Kavraki, “Simulated Knot Tying,” in Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), Washington, DC, USA, 2017, pp. 841–846.
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  7. A. Sudsang and L. E. Kavraki, “Part Orientation with a Force Field: Orienting Multiple Shapes using a Single Field,” in Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180), Maui, HI, USA, 2017, vol. 1, pp. 208–213.
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  8. A. Sudsang and L. E. Kavraki, “A Geometric Approach to Designing a Programmable Force Field with a Unique Stable Equilibrium for Parts in the Plane,” in Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164), Seoul, South Korea, 2017, vol. 2, pp. 1079–1085. This paper was a finalist for best conference paper award
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  9. L. E. Kavraki, “Part Orientation with Programmable Vector Fields: Two Stable Equilibria for Most Parts,” in Proceedings of International Conference on Robotics and Automation, Albuquerque, NM, USA, 2017, vol. 3, pp. 2446–2452.
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  10. J. Bohg, M. Ciocarlie, J. Civera, and L. E. Kavraki, “Big Data in Robotics,” Big Data, vol. 4, no. 4, pp. 195–196, Dec. 2016.
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  11. J. D. Hernández, M. Moll, E. Vidal Garcia, M. Carreras, and L. E. Kavraki, “Planning Feasible and Safe Paths Online for Autonomous Underwater Vehicles in Unknown Environments,” in 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Daejeon, South Korea, 2016, pp. 1313–1320.
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  12. N. T. Dantam, K. Bøndergaard, M. A. Johansson, T. Furuholm, and L. E. Kavraki, “Unix Philosophy and the Real World: Control Software for Humanoid Robots,” Frontiers in Robotics and AI, vol. 3, Mar. 2016.
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  13. L. E. Kavraki and M. Moll, “Editorial: Special Issue on the 2014 ‘Robotics: Science & Systems’ Conference,” International Journal of Robotics Research, vol. 3–4, no. 1–3, 2016.
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  14. Z. Kingston, N. Dantam, and L. E. Kavraki, “Kinematically constrained workspace control via linear optimization,” in 2015 IEEE-RAS 15th International Conference on Humanoid Robots (Humanoids), Seoul, South Korea, 2015, pp. 758–764.
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  15. C. Voss, M. Moll, and L. E. Kavraki, “A Heuristic Approach to Finding Diverse Short Paths,” in 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015, pp. 4173–4179.
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  16. L. E. Kavraki, D. Hsu, and J. Buchli, Eds., Robotics Science and Systems XI. 2015.
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  17. L. E. Kavraki and M. Likhachev, “Editorial: Special Issue on the 2014 ‘Robotics: Science & Systems’ Conference,” Autonomous Robots, vol. 39, no. 3, 2015.
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  18. D. Fox, L. E. Kavraki, and H. Kurniawati, Eds., Robotics Science and Systems X. 2014.
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  19. M. Moll, J. Bordeaux, and L. E. Kavraki, “Software for Project-Based Learning of Robot Motion Planning,” Computer Science Education, vol. 23, no. 4, pp. 332–348, Dec. 2013.
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  20. M. Moll, I. A. Sucan, J. Bordeaux, and L. E. Kavraki, “Teaching Motion Planning Concepts to Undergraduate Students,” in Advanced Robotics and its Social Impacts, Menlo Park, CA, USA, 2011.
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  21. D. K. Grady, M. Moll, C. Hegde, A. C. Sankaranarayanan, R. G. Baraniuk, and L. E. Kavraki, “Look Before You Leap: Predictive Sensing and Opportunistic Navigation,” in Workshop on Progress and Open Problems in Motion Planning at the IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, 2011.
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  22. M. Moll, J. Bordeaux, and L. E. Kavraki, “Teaching Robot Motion Planning,” Computers in Education (Special Issue on Novel Approaches to Robotics Education), vol. 20, no. 3, pp. 50–59, 2010.
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  23. R. B. Rusu, I. A. Sucan, B. P. Gerkey, S. Chitta, M. Beetz, and L. E. Kavraki, “Real-Time Perception-Guided Motion Planning for a Personal Robot,” in 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, St. Louis, MO, 2009, pp. 4245–4252.
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  24. K. I. Tsianos, D. Halperin, L. E. Kavraki, and J.-C. Latombe, “Robot Algorithms,” in Algorithms and Theory of Computation Handbook, Second., vol. 2, Boca Raton, FL: CRC Press, 2008.
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  25. E. Plaku and L. E. Kavraki, “Distributed Computation of the KNN Graph for Large High-Dimensional Point Sets,” Journal of Parallel and Distributed Computing, vol. 67, no. 3, pp. 346–359, Mar. 2007.
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  26. E. Plaku, K. E. Bekris, and L. E. Kavraki, “OOPS for Motion Planning: An Online Open-source Programming System,” in IEEE International Conference on Robotics and Automation (ICRA), Rome, Italy, 2007, pp. 3711–3716.
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  27. M. Moll and L. E. Kavraki, “Path Planning for Deformable Linear Objects,” IEEE Transactions on Robotics, vol. 22, no. 4, pp. 625–636, Aug. 2006.
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  28. K. E. Bekris, A. A. Argyros, and L. E. Kavraki, “Exploiting Panoramic Vision for Angle-Based Robot Navigation,” in Lecture Notes in Computer Science, Vol. 33, Springer, 2006, pp. 229–251.
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  29. A. A. Argyros, K. E. Bekris, S. C. Orphanoudakis, and L. E. Kavraki, “Robot Homing by Exploiting Panoramic Vision,” Autonomous Robots, vol. 19, no. 1, pp. 7–25, Jul. 2005.
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  30. M. Moll and L. E. Kavraki, “Path Planning for Variable Resolution Minimal-Energy Curves of Constant Length,” in Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain, 2005, pp. 2143–2147.
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  31. A. M. Ladd and L. E. Kavraki, “Using Motion Planning for Knot Untangling,” The International Journal of Robotics Research, vol. 23, no. 7–8, pp. 797–808, Aug. 2004.
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  32. M. Moll and L. E. Kavraki, “Path Planning for Minimal Energy Curves of Constant Length,” in IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA ’04. 2004, New Orleans, LA, USA, 2004, pp. 2826–2831.
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  33. K. E. Bekris, A. A. Argyros, and L. E. Kavraki, “Angle-Based Methods for Mobile Robot Navigation: Reaching the Entire Plane,” in IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA ’04. 2004, New Orleans, LA, USA, 2004, pp. 2373–2378.
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  34. A. M. Ladd and L. E. Kavraki, “Motion Planning for Knot Untangling,” in Algorithmic Foundations of Robotics V, Springer Tracks in Advanced Robotics, Springer Verlag, STAR 7, 2004, pp. 7–23.
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  35. F. Lamiraux and L. E. Kavraki, “Positioning Symmetric and Non-Symmetric Parts using Radial and Constant Force Fields,” in Algorithmic and Computational Robotics, Natick, MA, 2001, pp. 47–60.
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  36. F. Lamiraux and L. E. Kavraki, “Planning Paths for Elastic Objects under Manipulation Constraints,” The International Journal of Robotics Research, vol. 20, no. 3, pp. 188–208, Mar. 2001.
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  37. F. Lamiraux and L. E. Kavraki, “Positioning of Symmetric and Non-Symmetric Parts Using Radial and Constant Fields: Computation of All Equilibrium Configurations,” International Journal of Robotics Research, vol. 20, no. 8, pp. 635–659, 2001.
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  38. O. Brock and L. E. Kavraki, “Towards Real-Time Motion Planning in High Dimensional Spaces,” in Proceedings of The International Symposium on Robotics and Automation (ISRA), Monterey, Mexico, 2000.
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  39. F. Lamiraux and L. E. Kavraki, “Positioning and Orienting a Class of Symmetric Parts Using a Combination of a Unit-Radial and a Constant Force Fields,” in Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), San Francisco, CA, USA, 2000, vol. 1, pp. 178–183.
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  40. E. Anshelevich, S. Owens, F. Lamiraux, and L. E. Kavraki, “Deformable Volumes in Path Planning Applications,” in Proceedings 2000 ICRA. Millennium Conference. IEEE International Conference on Robotics and Automation. Symposia Proceedings (Cat. No.00CH37065), San Francisco, CA, USA, 2000, vol. 3, pp. 2290–2295.
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  41. K.-F. Bohringer, B. R. Donald, L. E. Kavraki, and F. Lamiraux, “Part Orientation with One or Two Stable Equilibria Using Programmable Vector Fields,” IEEE Transactions on Robotics and Automation, vol. 16, no. 2, pp. 157–170, 2000.
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  42. K.-F. Bohringer, B. R. Donald, L. E. Kavraki, and F. Lamiraux, “A Distributed, Universal Device for Planar Parts Feeding: Unique Part Orientation in Programmable Vector Fields,” in Distributed Manipulation, Kluwer Academic Publishers, 2000, pp. 1–29.
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  43. F. Lamiraux and L. E. Kavraki, “Path Planning for Elastic Plates Under Manipulation,” in Proceedings of The IEEE International Conference on Robotics and Automation (ICRA), Detroit, MI, 1999, vol. 1, pp. 151–156.
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  44. K.-F. Bohringer, B. R. Donald, L. E. Kavraki, and F. Lamiraux, “A Single Universal Force Field can Uniquely Orient Non-Symmetric Parts,” in Robotics Research: The 9th International Symposium, Springer, 1999, pp. 395–402.
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  45. L. E. Kavraki, F. Lamiraux, and C. Holleman, “Towards Planning for Elastic Objects,” in Robotics: The Algorithmic Perspective, Natick, MA, 1998, pp. 323–336.
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  46. D. Halperin, L. E. Kavraki, and J.-C. Latombe, “Robotics,” in Handbook of Discrete and Computational Geometry, Boca Raton, NY: CRC Press, 1997, pp. 755–779.
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  47. R. H. Wilson, L. E. Kavraki, J.-C. Latombe, and T. Lozano-Perez, “Two-Handed Assembly Sequencing,” The International Journal of Robotics Research, vol. 14, no. 4, pp. 335–350, Aug. 1995.
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  48. L. E. Kavraki, “On the Number of Equilibrium Placements of Mass Distributions in Elliptic Potential Fields,” Computer Science Department, Stanford University, 1559, 1995.
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  49. L. E. Kavraki, “Computation of Configuration Space Obstacles Using the Fast Fourier Transform,” IEEE Transactions on Robotics and Automation, vol. 11, no. 3, pp. 408–413, 1995.
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  50. L. E. Kavraki and M. N. Kolountzakis, “Partitioning an Assembly into Connected Parts is NP-hard,” Information Processing Letters, vol. 55, pp. 159–165, 1995.
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  51. L. E. Kavraki, J.-C. Latombe, and R. H. Wilson, “On the Complexity of Assembly Partitioning,” Information Processing Letters, vol. 48, no. 5, pp. 229–235, Dec. 1993.
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Planning from high-level specifications

  1. A. M. Wells, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “LTLf Synthesis on Probabilistic Systems,” Electronic Proceedings in Theoretical Computer Science, vol. 326, pp. 166–181, Sep. 2020.
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  2. Y. Wang, S. Chaudhuri, and L. E. Kavraki, “Online Partial Conditional Plan Synthesis for POMDPs with Safe-Reachability Objectives,” in Springer Proceedings in Advanced Robotics, 2020, pp. 127–143.
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  3. E. Vidal Garcia, M. Moll, N. Palomeras, J. D. Hernández, M. Carreras, and L. E. Kavraki, “Online Multilayered Motion Planning with Dynamic Constraints for Autonomous Underwater Vehicles,” in 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 8936–8942. (Top-3 finalist for best student paper award)
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  4. J. D. Hernández, M. Moll, and L. E. Kavraki, “Lazy Evaluation of Goal Specifications Guided by Motion Planning,” in 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 944–950.
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  5. K. He, A. M. Wells, L. E. Kavraki, and M. Y. Vardi, “Efficient Symbolic Reactive Synthesis for Finite-Horizon Tasks,” in 2019 International Conference on Robotics and Automation (ICRA), Montreal, QC, Canada, 2019, pp. 8993–8999. (Best paper award in Cognitive Robotics)
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  6. A. M. Wells, N. T. Dantam, A. Shrivastava, and L. E. Kavraki, “Learning Feasibility for Task and Motion Planning in Tabletop Environments,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1255–1262, Apr. 2019.
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  7. Y. Wang, S. Chaudhuri, and L. E. Kavraki, “Point-Based Policy Synthesis for POMDPs with Boolean and Quantitative Objectives,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 1860–1867, Apr. 2019.
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  8. K. He, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “Automated Abstraction of Manipulation Domains for Cost-Based Reactive Synthesis,” IEEE Robotics and Automation Letters, vol. 4, no. 2, pp. 285–292, Apr. 2019.
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  9. F. Lagriffoul, N. Dantam, C. Garrett, A. Akbari, S. Srivastava, and L. E. Kavraki, “Platform-Independent Benchmarks for Task and Motion Planning,” IEEE Robotics and Automation Letters, vol. 3, no. 4, pp. 3765–3772, Oct. 2018.
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  10. N. T. Dantam, S. Chaudhuri, and L. E. Kavraki, “The Task Motion Kit,” Robotics and Automation Magazine, vol. 25, no. 3, pp. 61–70, Sep. 2018.
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  11. N. T. Dantam, Z. K. Kingston, S. Chaudhuri, and L. E. Kavraki, “An Incremental Constraint-Based Framework for Task and Motion Planning,” The International Journal of Robotics Research, vol. 37, no. 10, pp. 1134–1151, Mar. 2018.
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  12. Y. Wang, S. Chaudhuri, and L. E. Kavraki, “Bounded Policy Synthesis for POMDPs with Safe-Reachability Objectives,” in Proceedings of the 17th International Conference on Autonomous Agents and Multiagent Systems, Stockholm, Sweden, 2018, pp. 238–246.
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  13. K. He, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “Reactive Synthesis For Finite Tasks Under Resource Constraints,” in 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Vancouver, BC, 2017, pp. 5326–5332.
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  14. W. Baker, Z. Kingston, M. Moll, J. Badger, and L. E. Kavraki, “Robonaut 2 and You: Specifying and Executing Complex Operations,” in 2017 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO), Austin, TX, USA, 2017.
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  15. N. T. Dantam, Z. K. Kingston, S. Chaudhuri, and L. E. Kavraki, “Incremental Task and Motion Planning: A Constraint-Based Approach,” in Robotics: Science and Systems XII, 2016.
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  16. M. Lahijanian, M. R. Maly, D. Fried, L. E. Kavraki, H. Kress-Gazit, and M. Y. Vardi, “Iterative Temporal Planning in Uncertain Environments with Partial Satisfaction Guarantees,” IEEE Transactions on Robotics, vol. 32, no. 3, pp. 583–599, Jun. 2016.
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  17. Y. Wang, N. T. Dantam, S. Chaudhuri, and L. E. Kavraki, “Task and Motion Policy Synthesis as Liveness Games,” in Proceedings of the International Conference on Automated Planning and Scheduling, 2016, pp. 536–540.
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  18. K. He, M. Lahijanian, L. E. Kavraki, and M. Y. Vardi, “Towards Manipulation Planning with Temporal Logic Specifications,” in 2015 IEEE International Conference on Robotics and Automation (ICRA), Seattle, WA, USA, 2015, pp. 346–352.
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  19. S. Nedunuri, S. Prabhu, M. Moll, S. Chaudhuri, and L. E. Kavraki, “SMT-Based Synthesis of Integrated Task and Motion Plans for Mobile Manipulation,” in Proceedings of the IEEE International Conference on Robotics and Automation, 2014, pp. 655–662.
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  20. M. R. Maly, M. Lahijanian, L. E. Kavraki, H. Kress-Gazit, and M. Y. Vardi, “Iterative Temporal Motion Planning for Hybrid Systems in Partially Unknown Environments,” in Proceedings of the 16th international conference on Hybrid systems: computation and control - HSCC ’13, Philadelphia, Pennsylvania, USA, 2013, pp. 353–362.
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  21. D. K. Grady, M. Moll, C. Hegde, A. C. Sankaranarayanan, R. G. Baraniuk, and L. E. Kavraki, “Multi-Robot Target Verification with Reachability Constraints,” in 2012 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), College Station, TX, USA, 2012, pp. 1–6.
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  22. D. K. Grady, M. Moll, C. Hegde, A. C. Sankaranarayanan, R. G. Baraniuk, and L. E. Kavraki, “Multi-Objective Sensor-Based Replanning for a Car-Like Robot,” in 2012 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR), College Station, TX, USA, 2012, pp. 1–6.
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  23. M. R. Maly and L. E. Kavraki, “Low-Dimensional Projections for SyCLoP,” in 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, Vilamoura-Algarve, Portugal, 2012, pp. 420–425.
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  24. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Falsification of LTL safety properties in hybrid systems,” International Journal on Software Tools for Technology Transfer, vol. 15, no. 4, pp. 305–320, May 2012.
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  25. I. A. Sucan and L. E. Kavraki, “Accounting for Uncertainty in Simultaneous Task and Motion Planning Using Task Motion Multigraphs,” in 2012 IEEE International Conference on Robotics and Automation, Saint Paul, MN, 2012, pp. 4822–4828.
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  26. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Falsification of LTL Safety Properties in Hybrid Systems,” in International Journal on Software Tools for Technology Transfer, York, UK, 2012, vol. 15, no. 4, pp. 305–320.
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  27. A. Bhatia, M. R. Maly, L. E. Kavraki, and M. Y. Vardi, “Motion Planning with Complex Goals,” IEEE Robotics and Automation Magazine, vol. 18, no. 3, pp. 55–64, Sep. 2011.
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  28. I. A. Sucan and L. E. Kavraki, “Mobile Manipulation: Encoding Motion Planning Options Using Task Motion Multigraphs,” in 2011 IEEE International Conference on Robotics and Automation, Shanghai, China, 2011, pp. 5492–5498.
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  29. I. A. Sucan and L. E. Kavraki, “On the Advantages of Using Task Motion Multigraphs for Efficient Mobile Manipulation,” in IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco, CA, 2011, pp. 4621–4626.
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  30. A. Bhatia, L. E. Kavraki, and M. Y. Vardi, “Motion Planning with Hybrid Dynamics and Temporal Goals,” in 49th IEEE Conference on Decision and Control (CDC), Atlanta, GA, USA, 2010, pp. 1108–1115.
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  31. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Motion Planning with Dynamics by a Synergistic Combination of Layers of Planning,” IEEE Transactions on Robotics, vol. 26, no. 3, pp. 469–482, Jun. 2010.
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  32. A. Bhatia, L. E. Kavraki, and M. Y. Vardi, “Sampling-Based Motion Planning with Temporal Goals,” in 2010 IEEE International Conference on Robotics and Automation, Anchorage, AK, 2010, pp. 2689–2696.
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  33. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Hybrid systems: from verification to falsification by combining motion planning and discrete search,” Formal Methods in System Design, vol. 34, pp. 157–182, 2009.
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  34. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Impact of Workspace Decompositions on Discrete Search Leading Continuous Exploration (DSLX) Motion Planning,” in 2008 IEEE International Conference on Robotics and Automation, Pasadena, CA, 2008, pp. 3751–3756.
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  35. E. Plaku, L. E. Kavraki, and M. Y. Vardi, “Hybrid Systems: From Verification to Falsification,” in International Conference on Computer Aided Verification (CAV), vol. 4590, Berlin, Germany: Lecture Notes in Computer Science, Springer-Verlag Heidelberg, 2007, pp. 468–481.
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Proteins and drugs

  1. D. A. Antunes, J. R. Abella, S. Hall-Swan, D. Devaurs, A. Conev, M. Moll, G. Lizée, and L. E. Kavraki, “HLA-Arena: a customizable environment for the structural modeling and analysis of peptide-HLA complexes for cancer immunotherapy,” JCO Clinical Cancer Informatics, vol. 4, no. 4, pp. 623–636, Sep. 2020.
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  2. J. R. Abella, D. A. Antunes, C. Clementi, and L. E. Kavraki, “Large-scale structure-based prediction of stable peptide binding to Class I HLAs using random forests,” Frontiers in Immunology, vol. 11, no. 1583, Jul. 2020.
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  3. D. Devaurs, D. A. Antunes, S. Hall-Swan, N. Mitchell, M. Moll, G. Lizée, and L. E. Kavraki, “Using parallelized incremental meta-docking can solve the conformational sampling issue when docking large ligands to proteins,” BMC Molecular and Cell Biology, vol. 20, no. 1, p. 42, Sep. 2019.
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  4. D. A. Antunes, J. R. Abella, D. Devaurs, M. M. Rigo, and L. E. Kavraki, “Structure-based methods for binding mode and binding affinity prediction for peptide-MHC complexes,” Current Topics in Medicinal Chemistry, vol. 18, no. 26, pp. 2239–2255, Jan. 2019.
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  5. D. A. Antunes, D. Devaurs, M. Moll, G. Lizée, and L. E. Kavraki, “General prediction of peptide-MHC binding modes using incremental docking: A proof of concept,” Scientific Reports, vol. 8, no. 1, p. 4327, Mar. 2018.
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  6. D. A. Antunes, M. Moll, D. Devaurs, K. R. Jackson, G. Lizée, and L. E. Kavraki, “DINC 2.0: a new protein-peptide docking webserver using an incremental approach,” Cancer Research, vol. 77, no. 21, pp. e55–57, Nov. 2017.
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  7. P. W. Finn, L. E. Kavraki, J.-C. Latombe, R. Motwani, and S. Venkat, “Search Techniques for Rational Drug Design,” in Proceedings Intelligent Information Systems. IIS’97, Grand Bahama Island, Bahamas, 2017, pp. 2–6.
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  8. P. K. Mandal, P. Morlacchi, J. M. Knight, T. M. Link, G. R. Lee, R. Nurieva, D. Singh, A. Dhanik, L. E. Kavraki, D. B. Corry, J. E. Ladbury, and J. S. McMurray, “Targeting the Src homology 2 (SH2) domain of signal transducer and activator of transcription 6 (STAT6) with cell-permeable, phosphatase-stable phosphopeptide mimics potently inhibits Tyr641 phosphorylation and transcriptional activity,” Journal of Medicinal Chemistry