Multi-agent motion planning with sporadic communications for collision avoidance

Boardman, Beth Leigh; Harden, Troy Anthony; Martinez, Sonia

doi:10.1016/j.ifacsc.2020.100126

Multi-agent motion planning with sporadic communications for collision avoidance

Journal Article · Thu Nov 26 00:00:00 EST 2020 · IFAC Journal of Systems and Control

DOI:https://doi.org/10.1016/j.ifacsc.2020.100126· OSTI ID:1727412

^[1]; ^[1]; Martinez, Sonia ^[2]

Los Alamos National Laboratory
Univ. of California, San Diego, CA (United States)

Here, a novel multi-vehicle motion planning and collision avoidance algorithm is proposed and analyzed. The algorithm aims to reduce the amount of onboard calculations and inter-agent communications needed for each vehicle to successfully navigate through an environment with static obstacles and reach their goals. To this end, each agent first calculates a path to the goal by means of an asymptotically optimal rapidly-exploring random tree (RRT*) with respect to the static obstacles. Then, other agents are treated as dynamic obstacles and potential collisions are determined by means of collision cones. Collision cones depend on the position and velocity from other agents and are grown conservatively between inter-agent communications. Based on the available information, each agent determines if a deconfliction maneuver is needed, if it can continue along its current path, or if communication is needed to make a decision about a conflict. With probability one, our algorithm guarantees that the agents keep from colliding with each other. Under an assumption on the existence of a solution for a vehicle to its goal, this algorithm also solves the planning problem with probability one. Simulations illustrate a group of agents successfully reaching their goal configurations and examine how the uncertainty affects the communication frequency of the multi-agent system.

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE; USDOE National Nuclear Security Administration (NNSA)

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1727412

Alternate ID(s):: OSTI ID: 1810982

Report Number(s):: LA-UR--18-29960

Journal Information:: IFAC Journal of Systems and Control, Journal Name: IFAC Journal of Systems and Control Journal Issue: C Vol. 15; ISSN 2468-6018

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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Multi-agent motion planning with sporadic communications for collision avoidance

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