相互測距を用いたマルチロボット協調自己位置推定と経路計画
Multi-Robot Collaborative Localization and Planning with Inter-Ranging
月面探査ロボット群がUWB測距を活用し、分散協調アルゴリズムで経路を計画して自己位置推定誤差を低減する手法を提案し、シミュレーションと実機で検証した。
著者: Derek Knowles, Adam Dai, Grace Gao
分類: cs.RO
原文アブストラクト
Robots often use feature-based image tracking to identify their position in their surrounding environment; however, feature-based image tracking is prone to errors in low-textured and poorly lit environments. Specifically, we investigate a scenario where robots are tasked with exploring the surface of the Moon and are required to have an accurate estimate of their position to be able to correctly geotag scientific measurements. To reduce localization error, we complement traditional feature-based image tracking with ultra-wideband (UWB) distance measurements between the robots. The robots use an advanced mesh-ranging protocol that allows them to continuously share distance measurements amongst each other rather than relying on the common "anchor" and "tag" UWB architecture. We develop a decentralized multi-robot coordination algorithm that actively plans paths based on measurement line-of-sight vectors amongst all robots to minimize collective localization error. We then demonstrate the emergent behavior of the proposed multi-robot coordination algorithm both in simulation and hardware to lower a geometry-based uncertainty metric and reduce localization error.
