A Flexible Hybrid Framework for Modeling Complex Manipulation Tasks

摘要：

Future service robots will need to perform a wide range of tasks using various objects. In order to perform complex tasks, robots require a suitable internal representation of the task. We propose a hybrid framework for representing manipulation tasks, which combines continuous motion planning and discrete task-level planning. In addition, we use a mid-level planner to optimize individual actions according to the plan. The proposed framework incorporates biologicallyinspired concepts, such as affordances and motor primitives, in order to ef.ciently plan for manipulation tasks. The .nal framework is modular, can generalize well to different situations, and is straightforward to expand. Our demonstrations also show how the use of affordances and mid-level planning can lead to improved performance.

作者: Oliver Kroemer Jan Peters

作者单位: Department of Empirical Inference at the Max Planck Institute for Intelligent Systems

会议类型: 国际会议

会议名称: 2011 IEEE International Conference on Robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)

会议地点: 上海

会议语种:英文

页码: 1856-1861

在线出版日期: 2011-05-09（万方平台首次上网日期，不代表论文的发表时间）