A hierarchical control architecture is proposed on the basis of an interaction model between efferent and afferent information in brain motor control. The model has five levels: motoneurons, premotor interneurons, pattern generator, parameter selection and action planning. The effectors including biophysical properties receive the commands from motoneurons. In the proposed architecture, the premotor interneurons and motoneurons are implemented as a servo module; the pattern generator corresponds to the motion planner; and the parameter selection is realized by adaptation module. The afferent information is the feedback signal and the efferent information corresponds motion command and parameter adaptation. Grasping and handling of a dynamically moving object are implemented on a DSP network with a high-speed vision, a dextrous hand and a 7 DOF manipulator. The results show responsive and flexible actions that exhibit the effectiveness of the proposed hierarchical modular structure.
|Number of pages||6|
|Journal||Proceedings of the IEEE Conference on Decision and Control|
|Publication status||Published - 2001|
|Event||40th IEEE Conference on Decision and Control (CDC) - Orlando, FL, United States|
Duration: 2001 Dec 4 → 2001 Dec 4