Mutli-robot path optimization based on DMPC

Mobile robot path planning refers to the design of the safely collision-free path with shortest distance and least time-consuming from the starting point to the end point by a mobile robot autonomously. At the application of multi-robot pattern formation, when the robot performs path planning in order to reach the target point, there are problems such as many iterations of the algorithm, large errors between the robot and the target point, long paths, and so on. To address these issues, this paper proposes an obstacle avoidance algorithm based on distributed model predictive control (DMPC). This model chooses acceleration as the input of the model, and establishes different constraints and objective functions depending on whether the robot detects other robots or obstacles. Optimal control is performed by optimizing the objective function to obtain the current optimal input. Finally, the effectiveness of the algorithm in this paper is verified by ex periments, and the results are compared with the Optimal Reciprocal Collision Avoidance (ORCA) algorithm, which shows the advantages of the algorithm in this chapter.