Independent navigation of multiple mobile robots with hybrid reciprocal velocity obstacles

Jamie Snape, Jur Van Den Berg, Stephen J. Guy, Dinesh Manocha

Research output: Chapter in Book/Report/Conference proceedingConference contribution

53 Scopus citations

Abstract

We present an approach for smooth and collision-free navigation of multiple mobile robots amongst each other. Each robot senses its surroundings and acts independently without central coordination or communication with other robots. Our approach uses both the current position and the velocity of other robots to predict their future trajectory in order to avoid collisions. Moreover, our approach is reciprocal and avoids oscillations by explicitly taking into account that the other robots also sense their surroundings and change their trajectories accordingly. We build on prior work related to velocity obstacles and reciprocal velocity obstacles and introduce the concept of hybrid reciprocal velocity obstacles for collision avoidance that takes into account the kinematics of the robots and uncertainty in sensor data. We apply our approach to a set of iRobot Create robots using centralized sensing and show natural, direct, and collision-free navigation in several challenging scenarios.

Original languageEnglish (US)
Title of host publication2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009
Pages5917-5922
Number of pages6
DOIs
StatePublished - Dec 11 2009
Event2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009 - St. Louis, MO, United States
Duration: Oct 11 2009Oct 15 2009

Publication series

Name2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009

Other

Other2009 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2009
Country/TerritoryUnited States
CitySt. Louis, MO
Period10/11/0910/15/09

Fingerprint

Dive into the research topics of 'Independent navigation of multiple mobile robots with hybrid reciprocal velocity obstacles'. Together they form a unique fingerprint.

Cite this