Optimal Paths for Polygonal Robots in SE(2)

Abstract

We consider planar navigation for a polygonal, holonomic robot in an obstacle-filled environment in SE(2). To determine the free space, we first represent obstacles as point clouds in the robot configuration space (C). A point-wise Minkowski sum of the robot and obstacle points is then calculated in C using obstacle points and robot convex hull points for varying robot configurations. Using graph search, we obtain a seed path, which is used in our novel method to compute overlapping convex regions for consecutive seed path chords. The resulting regions provide collision-free space useful for finding feasible trajectories that optimize a specified cost functional. The key contribution is the proposed method's ability to easily generate a set of convex, overlapping polytopes that effectively represent the traversable free space. This, in turn, lends itself to (a) efficient computation of optimal paths in ℝ3 and (b) extending these basic ideas to the special Euclidean space SE(2). We provide simulated examples and implement this algorithm on a KUKA youBot omnidirectional base.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 01, 2018
Source ID
10.1115/1.4038980

Entities

People

  • Dinesh Thakur
  • Mongying Hsieh-Cowley
  • Monroe Kennedy Iii
  • Subhrajit Bhattacharya
  • Vijay Kumar

Organizations

  • Defense Advanced Research Projects Agency
  • Lehigh University
  • National Science Foundation
  • University of Pennsylvania

Tags

Fields of Study

  • Computer science

Readers

  • Computational Modeling and Simulation
  • Graph Algorithms and Convex Optimization.
  • Robotics and Automation.

Technology Areas

  • AI & ML
  • AI & ML - Autonomous Systems
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Space
  • Space - Spacecraft Maneuvers