星凸制約最適化による可視性保証プランナと空中点検への応用
Star-Convex Constrained Optimization for Visibility Planning with Application to Aerial Inspection
可視空間を星凸ポリトープとしてモデル化し、可視性制約を緩和して軌道最適化を効率的に解く、空中点検向けの可視性保証プランナを提案した。
著者: Tianyu Liu, Qianhao Wang, Xingguang Zhong, Zhepei Wang, Chao Xu, Fu Zhang, Fei Gao
分類: cs.RO
原文アブストラクト
The visible capability is critical in many robot applications, such as inspection and surveillance, etc. Without the assurance of the visibility to targets, some tasks end up not being complete or even failing. In this paper, we propose a visibility guaranteed planner by star-convex constrained optimization. The visible space is modeled as star convex polytope (SCP) by nature and is generated by finding the visible points directly on point cloud. By exploiting the properties of the SCP, the visibility constraint is formulated for trajectory optimization. The trajectory is confined in the safe and visible flight corridor which consists of convex polytopes and SCPs. We further make a relaxation to the visibility constraints and transform the constrained trajectory optimization problem into an unconstrained one that can be reliably and efficiently solved. To validate the capability of the proposed planner, we present the practical application in site inspection. The experimental results show that the method is efficient, scalable, and visibility guaranteed, presenting the prospect of application to various other applications in the future.
