分散型リスク考慮型マルチターゲット追跡
Decentralized Risk-Aware Tracking of Multiple Targets
複数ロボットがリスクを考慮しつつ分散的に複数ターゲットを追跡する枠組みを提案し、集中型と同等の追跡精度とリスク回避を実現した。
著者: Jiazhen Liu, Lifeng Zhou, Ragesh Ramachandran, Gaurav S. Sukhatme, Vijay Kumar
分類: cs.RO
原文アブストラクト
We consider the setting where a team of robots is tasked with tracking multiple targets with the following property: approaching the targets enables more accurate target position estimation, but also increases the risk of sensor failures. Therefore, it is essential to address the trade-off between tracking quality maximization and risk minimization. In our previous work, a centralized controller is developed to plan motions for all the robots -- however, this is not a scalable approach. Here, we present a decentralized and risk-aware multi-target tracking framework, in which each robot plans its motion trading off tracking accuracy maximization and aversion to risk, while only relying on its own information and information exchanged with its neighbors. We use the control barrier function to guarantee network connectivity throughout the tracking process. Extensive numerical experiments demonstrate that our system can achieve similar tracking accuracy and risk-awareness to its centralized counterpart.
