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	Gain-optimization trajectory planning method for hyper-redundant manipulator with joint constraints 期刊论文 OAI收割 Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2019, 卷号: 27, 期号: 5, 页码: 1075-1086 作者: W.-R.Wang; K.-J.Liu; J.-L.Gu; A.Li; H.-R.Chu \| 收藏 \| 浏览/下载：24/0 \| 提交时间：2020/08/24 Monte Carlo methods,Industrial manipulators,Inverse kinematics,Inverse problems,Motion planning,Redundant manipulators,Robot programming,Trajectories,Velocity
	An improved artificial potential field method of trajectory planning and obstacle avoidance for redundant manipulators 期刊论文 OAI收割 International Journal of Advanced Robotic Systems, 2018, 卷号: 15, 期号: 5, 页码: 13 作者: Wang, W. R.; Zhu, M. C.; Wang, X. M.; He, S.; He, J. P. \| 收藏 \| 浏览/下载：36/0 \| 提交时间：2019/09/17 Trajectory planning attractive potential field velocity feedforward obstacle avoidance repulsive potential field cluttered environments mobile robots null-space navigation algorithms path Robotics
	Quadratic Programming-based Approach for Autonomous Vehicle Path Planning in Space 期刊论文 OAI收割 CHINESE JOURNAL OF MECHANICAL ENGINEERING, 2012, 卷号: 25, 期号: 4, 页码: 665-673 作者: Chen Y(陈洋); Han JD(韩建达); Wu HY(吴怀宇) 收藏 \| 浏览/下载：20/0 \| 提交时间：2012/10/24 path planning in three-dimensional space obstacle avoidance target pursuit relative velocity coordinates quadratic programming
	Curve fitting and optimal interpolation on CNC machines based on quadratic B-splines 期刊论文 OAI收割 SCIENCE CHINA-INFORMATION SCIENCES, 2011, 卷号: 54, 期号: 7, 页码: 1407-1418 作者: Zhang Mei; Yan Wei; Yuan ChunMing; Wang DingKang; Gao XiaoShan \| 收藏 \| 浏览/下载：19/0 \| 提交时间：2018/07/30 quadratic B-spline G01 codes feature point velocity planning interpolation
	Reentry guidance based on feedback linearization (EI CONFERENCE) 会议论文 OAI收割 2011 International Conference on Electronics, Communications and Control, ICECC 2011, September 9, 2011 - September 11, 2011, Ningbo, China Li D.-W. 收藏 \| 浏览/下载：30/0 \| 提交时间：2013/03/25 This paper presents a new reentry guidance algorithm for RLV (Reusable Launching Vehicle). The algorithm consists of two integrated components: trajectory planning algorithm and tracking algorithm. The most striking feature of algorithm here lies in that both planning and tracking are executed directly in height-velocity space which is different from the methodology of configuration of drag in traditional shuttle guidance. In the session of trajectory planning all trajectory constraints can be expressed with upper bound and lower bound in height-velocity space then a linear interpolation is carried to search the nominal trajectory satisfying the requirement of downrange and target constraints. Then the tracking algorithm uses feedback linearization method to track this nominal profile and meet all constraints. Another typical feature of this algorithm is the strategy of downrange extension using FPA (flight path angle) controller to fulfill the requirement of large downrange. Proper combination of planning-tracking algorithm and FPA controller can bring great flexibility and adaptability to reentry guidance. The algorithm is proved to be robust enough to accommodate the model error and noises in the dynamics. 2011 IEEE.
	全方位移动机器人控制与导航研究学位论文 OAI收割工学博士, 中国科学院自动化研究所: 中国科学院研究生院, 2006 作者: 邓旭玥收藏 \| 浏览/下载：68/0 \| 提交时间：2015/09/02 全方位移动机器人速度控制挤压力控制路径规划 omnidirectional mobile robot velocity control squeeze force control path planning