Formation control and obstacle avoidance for nonholonomic robots using decentralized MPC

In this paper, a decentralized model predictive control is proposed to solve the problem of formation stabilization and tracking for a group of nonholonomic mobile robots. Decentralized constrained control laws are developed by minimizing some objective functions. In the stabilization problem, the robots start from an arbitrary initial condition and reach a certain formation i.e. desired relative position and orientation. In the tracking problem under consideration, a desired trajectory is given to the leader of the formation. The followers keep a specified distance and orientation while following their leaders to keep a certain formation. Virtual force method is also used to avoid obstacles. All the agents in the formation avoid obstacles by producing a local virtual force with respect to their distance from the obstacle. Simulations for nonholonomic mobile robots formation stabilization and tracking with obstacle avoidance are performed to test the effectiveness of the proposed decentralized predictive control.

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