<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Moll, Mark</style></author><author><style face="normal" font="default" size="100%">Ioan Alexandru Sucan</style></author><author><style face="normal" font="default" size="100%">Janice Bordeaux</style></author><author><style face="normal" font="default" size="100%">Lydia E. Kavraki</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Teaching Motion Planning Concepts to Undergraduate Students</style></title><secondary-title><style face="normal" font="default" size="100%">IEEE Workshop on Advanced Robotics and its Social Impacts</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">kavrakilab</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2011</style></year></dates><abstract><style face="normal" font="default" size="100%">Motion planning is a central problem in robotics. Although it is an engaging topic for undergraduate students, it is difficult to teach, and as a result, the material is often only covered at an abstract level. Deep learning could be achieved by having students implement and test different algorithms. However, there is usually no time within a single class to have students completely implement several motion planning algorithms as they require the development of many lower-level data structures. We present an ongoing project to develop a teaching module for robotic motion planning centered around an integrated software environment. The module can be taught early in the undergraduate curriculum, after students have taken an introductory programming class.</style></abstract></record></records></xml>