Integrated Optimization of Simultaneous Target Assignment and Path Planning for Aerial Robot Swarm

Efficient task assignment and path planning are critical challenges in the coordination of swarm flying robots, particularly in complex environments. This paper introduces framework to simultaneously address both task allocation and path planning for swarm flying robots, with a focus on optimizing task distribution and ensuring collision-free trajectories. The proposed Simultaneous Allocation and Path Planning (SAPP) algorithm leverages local interactions and dynamic coordination among drones to achieve efficient task assignments and generate dynamically-feasible, collision-free paths for multiple multirotor robots. Comprehensive simulations, including both structured and unstructured scenarios, demonstrate the algorithm’s ability to dynamically adapt to changing environments, while maintaining optimal performance. The results highlight the robustness of the SAPP framework in ensuring task reallocation and trajectory optimization in multi-stage assignments, making it a promising solution for real-world swarm robotics applications. A supplemental animated simulation of this work is available at https://youtu.be/QAHZlkwhVDQ.