Multi-objective control of wheeled robot system using control barrier functions

被引:0
|
作者
Na X.-T. [1 ]
Zhao G.-L. [1 ]
Weng Z. [1 ]
Xia Y.-Q. [2 ]
机构
[1] College of Electronic Information Engineering, Inner Mongolia University, Huhhot
[2] School of Automation, Beijing Institute of Technology, Beijing
来源
Kongzhi yu Juece/Control and Decision | 2022年 / 37卷 / 09期
关键词
collision avoidance; connectivity; control barrier function; inequality constraint; multi-objective control; multi-robot cooperative control; nonholonomic constraint;
D O I
10.13195/j.kzyjc.2021.0309
中图分类号
学科分类号
摘要
A single controller is designed for a nonholonomic wheeled robot systems to synthesize formation, connectivity and collision avoidance, yielding a distributed control battier function (CBF) based controller, which is naturally relevant to the Lyapunov-like function. A novel class of Lyapunov-like barrier functions which encode the inequality constraints of connectivity and collision avoidance, is introduced into the controller. The corresponding barrier inequality constraints are proposed, and the robot achieves connectivity maintenance and collision avoidance objectives when ensuring the positive invariance of the constraint set. This method provides continues change of control velocity reducing the mechanical fatigue of the actuator. In addition, it can be extended to more secondary control objectives considering different control barrier functions. Moreover, the proposed cooperative control algorithm has no special requirements for formation, and is suitable for different formation requirements and communication topologies. Simulation results are included to verify the effectiveness of the cooperative control algorithm under different situations. © 2022 Northeast University. All rights reserved.
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页码:2235 / 2244
页数:9
相关论文
共 24 条
  • [1] Ma Y B, Dong H J, Sun W L, Et al., Thinking and exploration of pipeline intelligent perception technology during the epidemic of COVID-19, Oil & Gas Storage and Transportation, 39, 4, pp. 389-394, (2020)
  • [2] Ding Y N., The epidemic situation of COVID-19forces the digitalization transformation of urban management, China Industry & Information Technology, Z1, pp. 12-14, (2020)
  • [3] Tang C, Spong M W., Trajectory tracking with collision avoidance for nonholonomic vehicles with acceleration constraints and limited sensing, International Journal of Robotics Research, 33, 12, pp. 1569-1592, (2014)
  • [4] Yi G, Mao J X, Wang Y N, Et al., Moving target surrounding and obstacle avoidance control of multiple mobile robots, Chinese Journal of Scientific Instrument, 39, 2, pp. 11-20, (2018)
  • [5] Zhang Q B, Wang P, Chen Z H., Velocity space based concurrent obstacle avoidance and trajectory tracking for mobile robots, Control and Decision, 32, 2, pp. 358-362, (2017)
  • [6] Zhang H Q, Wu L H, Zhou Y, Et al., Self-organizing cooperative multi-target hunting by swarm robots in complex environments, Control Theory & Applications, 37, 5, pp. 1054-1062, (2020)
  • [7] Dong X Y, Xi Y G., Game theory based coverage control of multi-agent systems, Computer Simulation, 26, 10, pp. 148-152, (2009)
  • [8] Gan T, Xia B C., Barrier certificate generation for safety verification of continuous systems for a bounded time, Journal of Software, 27, 3, pp. 645-654, (2016)
  • [9] Yang X, Cao K, Liu B Z, Et al., Reachability set analysis of vehicle autonomous decision in multi-objective environment, Science Technology and Engineering, 19, 1, pp. 293-300, (2019)
  • [10] Wiel P, Allgower F., Constructive safety using control barrier functions, Proceedings of the 7th IFAC Symposiumon Nonlinear Control System, pp. 462-467, (2007)