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Collision and obstacle avoidance strategy for multi-agent systems with velocity dynamic programing

This paper conducts research on collision and obstacle avoidance of multi-agent systems without mapping ability, while the constrained agent can only detect obstacles within a limited distance, then a velocity programing strategy is proposed considering the lack of a high-resolution map and the challenge of the modeling of complex obstacles. Based on the detecting information of nearby members and obstacles, a discontinuous velocity programing space is constructed by imposing the constraints on the velocity. To obtain expansive programing space, two different ways are utilized to establish the velocity constraints of avoiding various obstacles. For obstacles that can be viewed as virtual circular obstacles, a barrier function is introduced to restrict the radial component of the velocity. As for the obstacle that can only be detected partially, we use the border lines to construct a velocity feasible domain, and the domain is approximated by the polygonal region using the convex theory. Then, the nominal velocity is utilized as the objective and a nonlinear dynamic programing regulator is proposed. Furtherly, velocity limits generated from the system kinematic constraints are incorporated into the regulator. Finally, three tests are carried out and the feasibility of the proposed regulator is verified.