都市水路における自律水上ロボット向け後退ホライズン多目的プランナ
A Receding Horizon Multi-Objective Planner for Autonomous Surface Vehicles in Urban Waterways
都市水路を航行する自律水上ロボットのため、センサ視野内の障害物を反映したグラフを逐次生成・探索する後退ホライズンプランナを提案し、辞書式最適化で衝突リスクなどの資源を階層的に扱う多目的経路計画を実現した。
著者: Tixiao Shan, Wei Wang, Brendan Englot, Carlo Ratti, Daniela Rus
分類: cs.RO
原文アブストラクト
We propose a novel receding horizon planner for an autonomous surface vehicle (ASV) performing path planning in urban waterways. Feasible paths are found by repeatedly generating and searching a graph reflecting the obstacles observed in the sensor field-of-view. We also propose a novel method for multi-objective motion planning over the graph by leveraging the paradigm of lexicographic optimization and applying it to graph search within our receding horizon planner. The competing resources of interest are penalized hierarchically during the search. Higher-ranked resources cause a robot to incur non-negative costs over the paths traveled, which are occasionally zero-valued. The framework is intended to capture problems in which a robot must manage resources such as risk of collision. This leaves freedom for tie-breaking with respect to lower-priority resources; at the bottom of the hierarchy is a strictly positive quantity consumed by the robot, such as distance traveled, energy expended or time elapsed. We conduct experiments in both simulated and real-world environments to validate the proposed planner and demonstrate its capability for enabling ASV navigation in complex environments.
