An Iterative Convex Optimization Approach for Minimum-Time Coordinated Path Planning with Obstacle Avoidance
Shuying Lyu, Xuhan Liu, Zhe Yang, Kai Ming Yang · 2025
This paper focuses on the minimum-time cooperative path planning problem of multiple loitering munitions with obstacle avoidance. By constructing a fixed-end-point normalized optimal control model, it is transformed into an equivalent parameterized convex optimization problem. Based on this model, an iterative convex optimization algorithm that does not require initial guess of flight time is designed. To handle the obstacle-avoidance and collision-avoidance constraints, a linearization method is used to transform the concave constraints into affine constraints, thus constructing a two-layer iterative convex optimization algorithm. Simulation results show that the proposed algorithm can effectively achieve collaborative path planning for multiple loitering munitions under minimum time constraints in three-dimensional space, satisfying obstacle avoidance, collision avoidance, and terminal attack angle constraints.