@inproceedings{33be2685145e48f0a94a4ff1429b57cd,
title = "Multi-Robot Cooperative Collision Avoidance with Conservatism Reduction",
abstract = "Multi-robot cooperative collision avoidance often employs control barrier functions to guarantee safety due to its formal safety guarantee. However, traditional methods impose overly conservative constraints, such as enforcing a circular safety region around each robot regardless of relative motion. In this paper, we introduce a binary parameter indicating whether the robot and an obstacle are close into the proposed controller, by reducing unnecessary collision avoidance to further reduce conservatism. We prove that this method preserves safety guarantees while enabling more aggressive maneuvers. Simulations in dense multi-robot scenarios demonstrate that our approach is more in line with the desired trajectory compared to baseline CBF methods, without compromising safety.",
keywords = "collision avoidance, multi-robot, optimization",
author = "Xiaoxiao Li and Hongpeng Wang",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 7th International Symposium on Robotics and Intelligent Manufacturing Technology, ISRIMT 2025 ; Conference date: 12-12-2025 Through 14-12-2025",
year = "2025",
doi = "10.1109/ISRIMT67769.2025.11413212",
language = "英语",
series = "2025 7th International Symposium on Robotics and Intelligent Manufacturing Technology, ISRIMT 2025",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "214--217",
booktitle = "2025 7th International Symposium on Robotics and Intelligent Manufacturing Technology, ISRIMT 2025",
address = "美国",
}