This paper considers the problem of completing assemblies of passive objects in nonconvex environments, cluttered with convex obstacles of unknown position, shape and size that satisfy a specific separation assumption. A differential drive robot equipped with a gripper and a LIDAR sensor, capable of perceiving its environment only locally, is used to position the passive objects in a desired configuration. The method combines the virtues of a deliberative planner generating high-level, symbolic commands, with the formal guarantees of convergence and obstacle avoidance of a reactive planner that requires little onboard computation and is used online. The validity of the proposed method is verified both with formal proofs and numerical simulations.
@article{arxiv.1709.05474,
title = {Technical Report: Sensor-Based Reactive Symbolic Planning in Partially Known Environments},
author = {Vasileios Vasilopoulos and William Vega-Brown and Omur Arslan and Nicholas Roy and Daniel E. Koditschek},
journal= {arXiv preprint arXiv:1709.05474},
year = {2018}
}
Comments
Technical Report accompanying the paper "Sensor-Based Reactive Symbolic Planning in Partially Known Environments" at ICRA '18 (11 pages, 6 figures)