QQ客服 官方微博 反馈留言

	Learning Task Transition from Standing-up to Walking for A Squatted Bipedal Humanoid Robot
	Luo, Dingsheng ; Deng, Yian ; Han, Xiaoqiang ; Hu, Fan ; Wu, Xihong
	2016
英文摘要	Robots can perform a number of complex tasks, some of which need to be executed consecutively in an effective way to form a smooth behavior. In this case, task transition technique is involved. Due to that there may exist large differences between two successive tasks, how to switch to the target task from current robot status smoothly and efficiently becomes an important problem, especially for those tasks that are with some strict constraints or necessary requirements, e.g. stability for a walking task. Unlike previous approaches such as task weighting and blending, priority handling, kinematic control, interpolation, etc., in this research, a learning paradigm based approach is proposed. With respect to the requirements of efficiency and smoothness, the task transition problem is formulated as a typical machine learning issue, where those constraints are taken as factors of an objective function the learning process based on. Through a specific task transition problem, which is from standing-up to walking for a squatted bipedal humanoid robot, our approach is demonstrated and evaluated. Experimental results on both simulated and hardware humanoid robot PKU-HR5.1 verify that the proposed approach is effective.; National Basic Research Program (973 Program) of China [2013CB329304]; National Natural Science Foundation of China [11590773, 61421062]; Key Program of National Social Science Foundation of China [12ZD119]; CPCI-S(ISTP); 1251-1256
语种	英语
出处	16th IEEE-RAS International Conference on Humanoid Robots (Humanoids)
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/470152]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Luo, Dingsheng,Deng, Yian,Han, Xiaoqiang,et al. Learning Task Transition from Standing-up to Walking for A Squatted Bipedal Humanoid Robot. 2016-01-01.

个性服务

查看访问统计

相关权益政策

暂无数据

收藏/分享

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。