異種ロボットチームによる適応的でリスクを考慮したターゲット追跡
Adaptive and Risk-Aware Target Tracking with Heterogeneous Robot Teams
センサ故障を引き起こす敵ターゲットを追跡する異種ロボットチームのため、性能最大化とセンサ保護のトレードオフを扱う予測・反応型制御フレームワークを提案した。
著者: Siddharth Mayya, Ragesh K. Ramachandran, Lifeng Zhou, Gaurav S. Sukhatme, Vijay Kumar
分類: cs.RO
原文アブストラクト
We consider a scenario where a team of robots with heterogeneous sensors must track a set of hostile targets which induce sensory failures on the robots. In particular, the likelihood of failures depends on the proximity between the targets and the robots. We propose a control framework that implicitly addresses the competing objectives of performance maximization and sensor preservation (which impacts the future performance of the team). Our framework consists of a predictive component -- which accounts for the risk of being detected by the target, and a reactive component -- which maximizes the performance of the team regardless of the failures that have already occurred. Based on a measure of the abundance of sensors in the team, our framework can generate aggressive and risk-averse robot configurations to track the targets. Crucially, the heterogeneous sensing capabilities of the robots are explicitly considered in each step, allowing for a more expressive risk-performance trade-off. Simulated experiments with induced sensor failures demonstrate the efficacy of the proposed approach.
