English

Collision-Free Multi Robot Trajectory Optimization in Unknown Environments using Decentralized Trajectory Planning

Robotics 2018-12-04 v1 Multiagent Systems

Abstract

Multi robot systems have the potential to be utilized in a variety of applications. In most of the previous works, the trajectory generation for multi robot systems is implemented in known environments. To overcome that we present an online trajectory optimization algorithm that utilizes communication of robots' current states to account to the other robots while using local object based maps for identifying obstacles. Based upon this data, we predict the trajectory expected to be traversed by the robots and utilize that to avoid collisions by formulating regions of free space that the robot can be without colliding with other robots and obstacles. A trajectory is optimized constraining the robot to remain within this region.The proposed method is tested in simulations on Gazebo using ROS.

Keywords

Cite

@article{arxiv.1812.00868,
  title  = {Collision-Free Multi Robot Trajectory Optimization in Unknown Environments using Decentralized Trajectory Planning},
  author = {Vijay Arvindh and Govind Aadithya R and Shravan Krishnan and Sivanathan K},
  journal= {arXiv preprint arXiv:1812.00868},
  year   = {2018}
}

Comments

6 pages,6 figures. To be Presented at 2018 IEEE 4th International Symposium in Robotics and Manufacturing Automation (ROMA)

R2 v1 2026-06-23T06:29:36.125Z