不確実性下での経路計画によるミリ波信号源の位置推定
Path Planning Under Uncertainty to Localize mmWave Sources
移動ロボットがミリ波信号源を効率的に探索するため、拡張カルマンフィルタによる位置推定と信念空間での経路計画を組み合わせた手法を提案し、シミュレーションで有効性を示した。
著者: Kai Pfeiffer, Yuze Jia, Mingsheng Yin, Akshaj Kumar Veldanda, Yaqi Hu, Amee Trivedi, Jeff Zhang, Siddharth Garg, Elza Erkip, Sundeep Rangan, Ludovic Righetti
分類: cs.RO
原文アブストラクト
In this paper, we study a navigation problem where a mobile robot needs to locate a mmWave wireless signal. Using the directionality properties of the signal, we propose an estimation and path planning algorithm that can efficiently navigate in cluttered indoor environments. We formulate Extended Kalman filters for emitter location estimation in cases where the signal is received in line-of-sight or after reflections. We then propose to plan motion trajectories based on belief-space dynamics in order to minimize the uncertainty of the position estimates. The associated non-linear optimization problem is solved by a state-of-the-art constrained iLQR solver. In particular, we propose a method that can handle a large number of obstacles (~300) with reasonable computation times. We validate the approach in an extensive set of simulations. We show that our estimators can help increase navigation success rate and that planning to reduce estimation uncertainty can improve the overall task completion speed.
