Hierarchical Distributed Control System for Multi-Agent Formation in Dynamic Environments

This paper addresses the problem of motion control of a multi-agent robotic formation operating in dynamic environments containing both static and dynamic obstacles. А hierarchical distributed control framework is proposed to coordinate the motion of multiple agents while maintaining a prescribed geometric formation during navigation. The developed architecture consists of four interconnected levels: an agent coordination level, a path planning level, a coordinated path-following level, and an individual agent motion control level. At the coordination level, a distributed mechanism based on the average consensus protocol is employed to generate a consistent estimate of the current position of the formation center using only local information exchange between neighboring agents. The path planning problem for the formation center is formulated as a nonconvex model predictive control (MPC) optimization problem that accounts for dynamic constraints and obstacle avoi dance requirements. To enable efficient numerical implementation, the resulting nonconvex problem is solved using a sequential convex programming (SCP) approach, which approximates the original problem through a sequence of convex optimization subproblems. For trajectory execution, distributed control algorithms are developed to ensure coordinated path following along both straight-line and circular segments of the planned route. These algorithms rely solely on local inter-agent communication and enable the formation to preserve the desired geometric configuration while moving along the path. The motion of individual agents is modeled using nonholonomic dynamics, which provides a sufficiently general representation applicable to a wide range of mobile robotic platforms, including ground, aerial, and marine vehicles. The proposed hierarchical distributed control strategy enables scalable and robust coordination of multi-agent formations in dynamic environments. The effectiveness of the developed algorithms is demonstrated through numerical simulations performed in the MATLAB environment, confirming stable formation motion and successful obstacle avoidance during navigation.

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