通信グラフ再構成によるマルチロボット目標追跡のレジリエンス向上
Resilience in multi-robot target tracking through reconfiguration
分散カルマンフィルタで目標追跡するマルチロボット系で、センサ品質が劣化したロボットの情報共有先を通信グラフの辺追加で再構成し、追跡能力を維持する手法を混合整数半正定値計画で定式化した。
著者: Ragesh K. Ramachandran, Nicole Fronda, Gaurav S. Sukhatme
分類: cs.RO
原文アブストラクト
We address the problem of maintaining resource availability in a networked multi-robot system performing distributed target tracking. In our model, robots are equipped with sensing and computational resources enabling them to track a target's position using a Distributed Kalman Filter (DKF). We use the trace of each robot's sensor measurement noise covariance matrix as a measure of sensing quality. When a robot's sensing quality deteriorates, the system's communication graph is modified by adding edges such that the robot with deteriorating sensor quality may share information with other robots to improve the team's target tracking ability. This computation is performed centrally and is designed to work without a large change in the number of active communication links. We propose two mixed integer semi-definite programming formulations (an 'agent-centric' strategy and a 'team-centric' strategy) to achieve this goal. We implement both formulations and a greedy strategy in simulation and show that the team-centric strategy outperforms the agent-centric and greedy strategies.
