Null-space-based modulated reference trajectory generator for multi-robots formation in obstacle environment

• Published in: ISA transactions Vol. 123; pp. 168 - 178
• Main Authors: Yao, Peng, Wei, Yunxia, Zhao, Zhiyao
• Format: Journal Article
• Language: English
• Published: United States Elsevier Ltd 01.04.2022
• Subjects: Nonlinear model predictive control (NMPC); Null-space-based modulated reference trajectory generator; Obstacle/collision avoidance; Three-dimensional formation; Null-space-based modulated reference trajectory generator; Obstacle/collision avoidance; Three-dimensional formation; Nonlinear model predictive control (NMPC)
• ISSN: 0019-0578; 1879-2022; 1879-2022
• DOI: 10.1016/j.isatra.2021.05.033

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. •The NMPC is used as the framework of multi-robot formation in obstacle environment.•Null-space-based modulated reference trajectory generator designs the desired state.•The robots avoid obstacles without violating the stability of formation system.