Kavraki Lab

Physical and Biological Computing

Keywords:

Abstract:

This paper provides proof-of-concept that state-of-the-art
sampling-based motion planners that are tightly integrated with a
physics-based simulator can compute paths that can be executed by a
physical robotic system. Such a goal has been the subject of
intensive research during the last few years and reflects the desire
of the motion planning community to produce paths that are directly
relevant to realistic mechanical systems and do not need a huge
post-processing step in order to be executed on a robotic
platform. To evaluate this approach, a recently developed motion
planner is used to compute paths for a modular robot constructed
from seven modules. These paths are then executed on hardware and
compared with the paths predicted by the planner. For the system
considered, the planner prediction and the paths achieved by the
physical robot match, up to small errors. This work reveals the
potential of modern motion planning research and its implications in
the design and operation of complex robotic platforms.