Joint Communication and Motion Planning for Cobots
Abstract
The increasing deployment of robots in co-working scenarios with humans has revealed complex safety and efficiency challenges in the computation robot behavior. Movement among humans is one of the most fundamental -- and yet critical -- problems in this frontier. While several approaches have addressed this problem from a purely navigational point of view, the absence of a unified paradigm for communicating with humans limits their ability to prevent deadlocks and compute feasible solutions. This paper presents a joint communication and motion planning framework that selects from an arbitrary input set of robot's communication signals while computing robot motion plans. It models a human co-worker's imperfect perception of these communications using a noisy sensor model and facilitates the specification of a variety of social/workplace compliance priorities with a flexible cost function. Theoretical results and simulator-based empirical evaluations show that our approach efficiently computes motion plans and communication strategies that reduce conflicts between agents and resolve potential deadlocks.
Cite
@article{arxiv.2109.14004,
title = {Joint Communication and Motion Planning for Cobots},
author = {Mehdi Dadvar and Keyvan Majd and Elena Oikonomou and Georgios Fainekos and Siddharth Srivastava},
journal= {arXiv preprint arXiv:2109.14004},
year = {2022}
}