Sensor-based reactive symbolic planning in partially known environments

• Main Authors: Vasilopoulos, Vasileios (Author), Vega-Brown, William R (Author), Arslan, Omur (Author), Roy, Nicholas (Author), Koditschek, Daniel E. (Author)
• Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor)
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers (IEEE), 2020-06-19T14:35:30Z.
• Subjects: Article
• Online Access: Get fulltext

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.
ARL/GDRS RCTA project (agreement no. W911NF-1020016)
AFRL (grant no. FA865015D1845)