Experimental Validation of a Multirobot Distributed Receding Horizon Motion Planning Approach

This paper addresses the problem of motion planning for a multirobot system in a partially known environment where conditions such as uncertainty about robots' positions and communication delays are real. In particular, we detail the use of a Distributed Receding Horizon Approach that guarantee...

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Bibliographic Details
Published in:2018 15th International Conference on Control, Automation, Robotics and Vision (ICARCV) pp. 1640 - 1646
Main Authors: Filho, Jose M. Mendes, Lucet, Eric, Filliat, David
Format: Conference Proceeding
Language:English
Published: IEEE 01.11.2018
Subjects:
Collision avoidance
Optimization
Planning
Programming
Robot sensing systems
Trajectory
Online Access:Get full text
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Summary:This paper addresses the problem of motion planning for a multirobot system in a partially known environment where conditions such as uncertainty about robots' positions and communication delays are real. In particular, we detail the use of a Distributed Receding Horizon Approach that guarantees collision avoidance with static obstacles and between robots communicating with each other. Underlying optimization problems are solved by using a Sequential Least Squares Programming algorithm. Experiments with real nonholonomic mobile platforms are performed. The proposed framework is compared with the Dynamic Window approach to motion planning in a single robot setup. A second experiment shows results for a multirobot case using two robots where collision is avoided even in presence of significant localization uncertainties.
DOI:10.1109/ICARCV.2018.8581365