Integrated task and motion planning in belief space 论文

2013The International Journal of Robotics Research引用 329
Robotic Path Planning AlgorithmsRobot Manipulation and LearningAI-based Problem Solving and Planning

详细信息

发表期刊/会议
The International Journal of Robotics Research
发表日期
2013-07-15
发表年份
2013

关键词

Robotic Path Planning AlgorithmsRobot Manipulation and LearningAI-based Problem Solving and Planning

摘要

We describe an integrated strategy for planning, perception, state estimation and action in complex mobile manipulation domains based on planning in the belief space of probability distributions over states using hierarchical goal regression (pre-image back-chaining). We develop a vocabulary of logical expressions that describe sets of belief states, which are goals and subgoals in the planning process. We show that a relatively small set of symbolic operators can give rise to task-oriented perception in support of the manipulation goals. An implementation of this method is demonstrated in simulation and on a real PR2 robot, showing robust, flexible solution of mobile manipulation problems with multiple objects and substantial uncertainty.