Decentralized multi-robot formation control in environments with non-convex and dynamic obstacles based on path planning algorithms
L. Enrique Ruiz-Fernández, Javier Ruiz‐León, David Gómez‐Gutiérrez, Rafael Murrieta-Cid
- 发表年份
- 2025
- 引用次数
- 6
- 访问权限
- 开放获取
摘要
Abstract In this paper, we propose a new strategy to solve the multi-robot formation problem. Considering a set of holonomic robots, a decentralized algorithm is proposed to guide the robots to achieve a predefined formation while avoiding collisions with non-convex obstacles, dynamic obstacles, and other robots. Local collision avoidance is achieved using a variant of the well-known ORCA (optical reciprocal collision avoidance) algorithm. We modify this algorithm to ensure the continuity of the robots’ controls (velocities). The implementation of an online replanning algorithm, RRT , is essential to guide the robots and prevent them from getting stuck in minima. The resulting method guarantees formation convergence, and several simulations are presented to illustrate its effectiveness.
关键词
相关论文
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