TY - GEN
T1 - Distributed time-varying formation and optimization with inequality constraints of a multi-robot system
AU - Sun, Chao
AU - Feng, Zhi
AU - Hu, Guoqiang
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - In this paper, we consider a distributed time-varying formation and optimization problem for a group of robots with uncertain Euler-Lagrange dynamics. The robots are required to keep a time-varying formation as well as optimizing a quadratic objective function that is composed of the state information of all the robots with linear inequality constraints. The well known formation tracking problem can be viewed as a special case of the proposed optimization based framework, provided that the objective function is properly selected and each robot has access to the formation tracking leader's trajectory. The problem is mathematically reformulated as a distributed time-varying optimization problem, where the time-varying formation task is viewed as a time-varying equality constraint. A quadratic penalty function is used to deal with the equality constraint and a third-order differentiable penalty function is introduced to deal with the inequality constraint. A numerical example is provided to show the effectiveness and efficiency of the proposed method.
AB - In this paper, we consider a distributed time-varying formation and optimization problem for a group of robots with uncertain Euler-Lagrange dynamics. The robots are required to keep a time-varying formation as well as optimizing a quadratic objective function that is composed of the state information of all the robots with linear inequality constraints. The well known formation tracking problem can be viewed as a special case of the proposed optimization based framework, provided that the objective function is properly selected and each robot has access to the formation tracking leader's trajectory. The problem is mathematically reformulated as a distributed time-varying optimization problem, where the time-varying formation task is viewed as a time-varying equality constraint. A quadratic penalty function is used to deal with the equality constraint and a third-order differentiable penalty function is introduced to deal with the inequality constraint. A numerical example is provided to show the effectiveness and efficiency of the proposed method.
UR - https://www.scopus.com/pages/publications/85074277936
U2 - 10.1109/AIM.2019.8868686
DO - 10.1109/AIM.2019.8868686
M3 - 会议稿件
AN - SCOPUS:85074277936
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 629
EP - 634
BT - Proceedings of the 2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM 2019
Y2 - 8 July 2019 through 12 July 2019
ER -