Presidential Young Investigator Award: Robot Motion Planning

利用位形空间展开机器人运动规划的研究。当前的规划方法没有考虑到环境模型中可能出现的严重误差，例如未建模的障碍物或表面缺陷。在实验室和工厂等控制良好的环境之外，这类问题相当普遍。挑战在于尽早发现错误，并在不需要完全重新规划的情况下采取纠正措施。此外，这种方法将扩展到规划处理多个运动对象的运动不完全知道提前。其理念是，只要其他对象在其预期范围内移动，就能够保证存在一个实现目标的计划。这两种扩展都建立在这样一个基本思想的基础上：提前计划并不需要确切地知道环境的状态。

An investigation of robot motion planning will be expanded using configuration space. Current planning methods do not take into account the possibility of gross errors in the environment model, such as unmodeled obstacles or surface defects. These kinds of problems are quite common outside of well-controlled environments such as laboratories and factories. The challenge is to detect the error as early as possible and to undertake corrective action without requiring complete re-planning. Further, this approach will be extended to planning to deal with multiple moving objects whose motions are not completely known in advance. The idea is to be able to guarantee that there exists a plan that achieves the goal as long as the other objects move within their expected bounds. Both of these extensions will build on the basic idea that to plan ahead one does not need to know the state of the environment exactly.