センサ故障に強い分散マルチロボット多目標追跡のための通信網再構成
Resilience in multi-robot multi-target tracking with unknown number of targets through reconfiguration
未知数の目標を分散PHDフィルタで追跡するマルチロボット系で、センサ品質低下時に通信リンク数を抑えつつ情報共有を再構成するMISDP手法を4種提案し、シミュレーションで検証した。
著者: Ragesh K. Ramachandran, Nicole Fronda, Gaurav S. Sukhatme
分類: cs.RO, cs.MA, cs.SY, eess.SY
原文アブストラクト
We address the problem of maintaining resource availability in a networked multi-robot team performing distributed tracking of unknown number of targets in an environment of interest. Based on our model, robots are equipped with sensing and computational resources enabling them to cooperatively track a set of targets in an environment using a distributed Probability Hypothesis Density (PHD) filter. We use the trace of a robot's sensor measurement noise covariance matrix to quantify its sensing quality. While executing the tracking task, if a robot experiences sensor quality degradation, then robot team's communication network is reconfigured such that the robot with the faulty sensor may share information with other robots to improve the team's target tracking ability without enforcing a large change in the number of active communication links. A central system which monitors the team executes all the network reconfiguration computations. We consider two different PHD fusion methods in this paper and propose four different Mixed Integer Semi-Definite Programming (MISDP) formulations (two formulations for each PHD fusion method) to accomplish our objective. All four MISDP formulations are validated in simulation.
