论文标题

在动态不确定性下的安全任务计划

Safe Mission Planning under Dynamical Uncertainties

论文作者

Lu, Yimeng, Kamgarpour, Maryam

论文摘要

本文考虑在不确定的动态环境中考虑安全的机器人任务计划。此问题出现在监视,紧急救援和自动驾驶等应用中。由于建模并将动态不确定性集成到安全的计划框架中,并以计算易于处理能的方式找到解决方案,这是一个具有挑战性的问题。在这项工作中,我们首先为动态不确定性开发了概率模型。然后,我们提供一个框架来生成一条路径,通过合并不确定性模型来最大化复杂任务的安全性。我们还设计了一种蒙特卡洛方法来有效地获得安全路径。最后,我们评估了我们的方法的性能,并将其与一些案例研究中的潜在替代方案进行了比较。

This paper considers safe robot mission planning in uncertain dynamical environments. This problem arises in applications such as surveillance, emergency rescue, and autonomous driving. It is a challenging problem due to modeling and integrating dynamical uncertainties into a safe planning framework, and finding a solution in a computationally tractable way. In this work, we first develop a probabilistic model for dynamical uncertainties. Then, we provide a framework to generate a path that maximizes safety for complex missions by incorporating the uncertainty model. We also devise a Monte Carlo method to obtain a safe path efficiently. Finally, we evaluate the performance of our approach and compare it to potential alternatives in several case studies.

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