Yao Peng, Wei Yunxia, Zhao Zhiyao
College of Engineering, Ocean University of China, Qingdao 266100, China.
Key Laboratory of Industrial Internet and Big Data, China National Light Industry, Beijing Technology and Business University, Beijing 100048, China; School of Artificial Intelligence, Beijing Technology and Business University, Beijing 100048, China.
ISA Trans. 2022 Apr;123:168-178. doi: 10.1016/j.isatra.2021.05.033. Epub 2021 May 26.
This paper devotes to the three-dimensional formation problem of multi-robots in obstacle environment. Given the desired formation pattern and the group trajectory, it is formulated as obtaining the control inputs of robots so that the formation errors converge to zero gradually with obstacle/collision avoidance subject to state and input constraints. The well-known nonlinear model predictive control (NMPC) can be utilized as the solution framework due to its stability and robustness according with the reference state vector. Particularly, the null-space-based modulated reference trajectory generator is proposed to modulate the reference state vector of each robot. The original reference velocity, obtained from the Lyapunov stability theory, will be modulated quantitatively in the presence of each obstacle, and then the modulated velocities are integrated effectively on the basis of null space. From the perspective of trajectory generator, it is proven that the robots will avoid obstacles or collision without violating the stability of formation system. Finally the simulation results demonstrate the high efficiency and strong robustness of our method.
本文致力于研究多机器人在障碍环境中的三维编队问题。给定期望的编队模式和群组轨迹，该问题被表述为获取机器人的控制输入，以使编队误差在避免障碍/碰撞的情况下，在状态和输入约束条件下逐渐收敛到零。由于其根据参考状态向量具有稳定性和鲁棒性，著名的非线性模型预测控制（NMPC）可被用作解决方案框架。特别地，提出了基于零空间的调制参考轨迹生成器来调制每个机器人的参考状态向量。从李雅普诺夫稳定性理论获得的原始参考速度，将在每个障碍物存在时进行定量调制，然后在零空间的基础上有效地积分调制后的速度。从轨迹生成器的角度来看，证明了机器人将避免障碍或碰撞而不违反编队系统的稳定性。最后，仿真结果证明了我们方法的高效性和强鲁棒性。
