机器人Issue(3)：309-315,7.DOI:10.3724/SP.J.1218.2014.00309
机器人模仿学习的非接触观测控制图模型
Cybernetic-Graphic Model for Robot Imitation Learning Based on Non-contact Observation
摘要
Abstract
The cybernetic graphic model (CGM), a new model of behavioral representation and reproduction, based on non-contact observation for robot imitation learning is proposed. The human-robots relationship is built for imitating the behaviors from demonstration of human, and the pre-condition of imitation learning is analyzed to be that differential motions of end-effector of system are used as the behavioral primitives. Architecture of CGM and the learning method based on visual observation sequences are proposed. The segmenting method of sequences based on accumulating and instantaneous correlation function for generation of graphic structure of CGM and the learning method of behavioral primitive target based on RBF (radial basis function) networks are proposed. The brush drawing and object grasping experiments are performed with different types and degrees of freedom of robots. The results show that the proposed CGM based on visual observation can represent and reproduce different levels and types of behaviors, and is powerful in generalization, generality and utility of imitation learning.关键词
机器人行为/模仿学习/控制图模型/非接触观测信息/视觉观测Key words
robot behavior/imitation learning/cybernetic graphic model/non-contact observation/vision observation分类
信息技术与安全科学引用本文复制引用
杨俊友,马乐,白殿春,东俊光..机器人模仿学习的非接触观测控制图模型[J].机器人,2014,(3):309-315,7.基金项目
国家自然科学基金资助项目（51075281）；教育部高等学校博士学科点专项科研基金资助项目（20112102110002）；辽宁省自然科学基金资助项目（201102163）． （）
