论文标题
恒星凸限制为可见性计划的优化，并适用于航空检查
Star-Convex Constrained Optimization for Visibility Planning with Application to Aerial Inspection
论文作者
论文摘要
可见功能在许多机器人应用中至关重要，例如检查和监视等。在没有可见目标的情况下，某些任务最终并没有完成甚至失败。在本文中，我们建议通过Star-Convex受约束优化的可见性保证的计划者。可见空间本质上是建模为星凸多层（SCP），并通过直接在点云上找到可见点而生成。通过利用SCP的属性，可以为轨迹优化制定可见性约束。该轨迹限制在安全可见的飞行走廊中，该走廊由凸多型和SCP组成。我们进一步放松了可见性限制，并将约束轨迹优化问题转变为一个可以可靠有效地解决的不受约束的问题。为了验证拟议的计划者的能力，我们在现场检查中介绍了实际应用。实验结果表明，该方法是有效的，可扩展的和可见性的，将来将应用于其他各种应用程序的前景。
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.
