A dynamics based two-stage path model for the docking navigation of a self-assembly modular robot (Sambot)

被引:10
|
作者
Wei, Hong-Xing [1 ]
Li, Hai-Yuan [1 ]
Guan, Yong [2 ]
Li, Yong-Dong [3 ,4 ]
机构
[1] Beihang Univ, Sch Mech Engn & Automat, Beijing 100191, Peoples R China
[2] Capital Normal Univ, Coll Informat Engn, Beijing 100048, Peoples R China
[3] Capital Normal Univ, Joint Lab High Performance Robots & Safety Verifi, Beijing 100048, Peoples R China
[4] Acad Armored Force Engn, Dept Mech Engn, Beijing 100072, Peoples R China
基金
中国国家自然科学基金; 国家高技术研究发展计划(863计划);
关键词
Self-assembly; Wheeled mobile robot; Docking; Navigation; Lagrangian dynamics; TIME-OPTIMAL TRAJECTORIES;
D O I
10.1017/S0263574714002422
中图分类号
TP24 [机器人技术];
学科分类号
080202 ; 1405 ;
摘要
Autonomous docking is a focus of research in the field of self-assembly robots. Navigation is a significant stage in the process of autonomous docking between two robotic modules; it determines the efficiency of docking and even the success and failure of the docking task. In most cases, it is too difficult to simultaneously satisfy both linear and angular displacement constraints in a single dynamic numerical computation process. In the present paper, the navigation process is divided into two stages: first, the angular displacement constraint is satisfied, and then the linear displacement condition is fulfilled. In this way, the constraints are loosened and the difficulty of numerical computation is thereby effectively reduced. This two-stage docking navigation model is the main contribution of the present work. By taking the non-holonomic nature of the navigation behavior into consideration, both kinematic and dynamic analyses are performed, and the voltage data of the DC motors required by the two-stage docking navigation are obtained. Finally, docking navigation experiments are completed on a self-assembly modular robot named Sambot. It is verified that the present two-stage strategy is effective in controlling the docking navigation process.
引用
收藏
页码:1517 / 1528
页数:12
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