论文标题
朝着信仰空间导航的多机器人任务运动计划
Towards Multi-Robot Task-Motion Planning for Navigation in Belief Space
论文作者
论文摘要
在大型知识域中运行的自主机器人需要在离散（任务）空间和连续（运动）空间中进行计划。一方面，在知识密集型域中，机器人必须在最高级别上进行推理，例如要导航到要捡起的对象及其属性；另一方面，必须在控制器执行级别检查各个导航任务的可行性。此外，使用多个机器人可以通过执行相同任务的单个机器人提供增强的性能功能。为此，我们提出了一个集成的多机器人任务运动计划框架，用于在知识密集型域中导航。特别是，我们考虑了一个分布式的多机器人设置，该设置结合了机器人之间的相互观察。该框架旨在在运动和感知不确定性下进行运动计划，这正式称为信仰空间规划。讨论了基本方法及其局限性，为改进和未来工作提供了建议。我们验证了模拟方法的关键方面。
Autonomous robots operating in large knowledgeintensive domains require planning in the discrete (task) space and the continuous (motion) space. In knowledge-intensive domains, on the one hand, robots have to reason at the highestlevel, for example the regions to navigate to or objects to be picked up and their properties; on the other hand, the feasibility of the respective navigation tasks have to be checked at the controller execution level. Moreover, employing multiple robots offer enhanced performance capabilities over a single robot performing the same task. To this end, we present an integrated multi-robot task-motion planning framework for navigation in knowledge-intensive domains. In particular, we consider a distributed multi-robot setting incorporating mutual observations between the robots. The framework is intended for motion planning under motion and sensing uncertainty, which is formally known as belief space planning. The underlying methodology and its limitations are discussed, providing suggestions for improvements and future work. We validate key aspects of our approach in simulation.
