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
Related papers
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002