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Decentralized Multi-robot Collision-free Path Following Based on Time-varying Artificial Vector Fields and MPC-ORCA

Elias José de Rezende Freitas, Arthur da C. Vangasse, Guilherme V. Raffo, Luciano C. A. Pimenta

Year
2023
Citations
5

Abstract

This work focuses on the solution for multi-agent, collision-free, time-varying path-following problems in 3D spaces. The proposed solution is based on using time-varying artificial vector fields to generate velocity references for single agents. A distributed Model Predictive Control (MPC) scheme is employed, taking into account the system’s dynamics and collision avoidance features, enabling the multi-robot system to follow the dynamic field without collisions and providing great computational efficiency. More specifically, Optimal Reciprocal Collision Avoidance (ORCA) algorithm is used to set constraints, yielding a novel MPC-ORCA approach, for efficient collision avoidance in the multi-agent scenario. Simulation scenarios are used to validate and compare the proposed approach with traditional methods, highlighting its improvements.

Keywords

Collision avoidanceCollisionComputer scienceModel predictive controlRobotPath (computing)Control theory (sociology)Set (abstract data type)Scheme (mathematics)Field (mathematics)

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