Motion planning for humanoid robot anticipating environmental changes

仿人机器人预测环境变化的运动规划

基本信息

批准号：
16F16701
负责人：
吉田英一
金额：
$ 1.41万
依托单位：
National Institute of Advanced Industrial Science and Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for JSPS Fellows
财政年份：
2016
资助国家：
日本
起止时间：
2016-11-07 至 2019-03-31
项目状态：
已结题

项目摘要

We have developed a new motion planning framework using the mathematical concept of a quotient-space, through removal of a dimension to improve the efficiency of computation. A quotient-space is a simplified space, which is created by declaring points in a space as being equivalent, and then grouping them together into a single point of the quotient-space. We realized this simplification through the idea of nesting robots in each other.Our approach is general to be applied to any robot. Fo a manipulator arm, we nest a series of lower-dimensional manipulator arms inside the original arm, whereby each lower-dimensional arm is created by removing a link of the arm. This nesting of robots creates a series of quotient-spaces, which are all nested inside the original configuration space.We have subsequently developed a new algorithm, called the quotient-space roadmap planner (QMP), which is able to exploit quotient-spaces. Our planner is unique in that it uses simplifications while being complete. Being complete means that we will find a path for a planning problem, whenever one exists.Our algorithm QMP works by first decomposing the configuration into its quotient-spaces. Then we start growing a graph on the lowest-dimensional quotient-space until we find a feasible path. Once such a path has been found, we start growing a second graph on the next quotient-space. Both graphs are simultaneously grown until a feasible path is found on the next quotient-space. This process is continued until we find a path on the configuration space itself.

我们已经使用商空间的数学概念开发了一个新的运动计划框架，该概念是通过删除维度来提高计算效率的。商空间是一个简化的空间，它是通过在空间中声明要点等效而创建的，然后将它们分组为单位空间的单个点。我们通过彼此嵌套机器人的想法实现了这种简化。我们的方法通常应用于任何机器人。在操纵器臂上，我们在原始手臂内筑巢一系列较低维的操纵器臂，从而通过拆下手臂的链路来创建每个较低维度的手臂。这种机器人的嵌套会产生一系列的商空间，这些空间都嵌在原始配置空间内。我们随后开发了一种新算法，称为商空间路线图计划器（QMP），该算法能够利用商空间。我们的计划者是独一无二的，因为它在完成时使用了简化。完整意味着我们将在一个存在的情况下找到计划问题的路径。我们的算法QMP首先将配置分解为其商空间来起作用。然后，我们开始在最低维商空间上生长图形，直到找到可行的路径。一旦找到了这样的路径，我们就会在下一个商空间上增加第二个图。这两个图都同时生长，直到在下一个商空间上找到可行的路径。继续此过程，直到我们在配置空间本身上找到路径。

项目成果

期刊论文数量（0）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Quotient-Space Motion Planning

DOI：
10.1109/iros.2018.8593554
发表时间：
2018-07
期刊：
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
影响因子：
0
作者：
A. Orthey;Adrien Escande;E. Yoshida
通讯作者：
A. Orthey;Adrien Escande;E. Yoshida