2023/10/04 by Akash Kopparam Sreedhara, Sreedhara, Akash Kopparam, Deepesh Padala +9
Computer Science · Engineering · #FOS: Computer and information sciences #Multiagent Systems (cs.MA) #Robotic Path Planning Algorithms #Robotics (cs.RO) #UAV Applications and Optimization #Vehicle Routing Optimization Methods
paper · pdf · doi:10.48550/arxiv.2310.02726
openalex publication_date 2023/10/04 · openalex created_date 2023/10/06 · openalex updated_date 2026/07/28
Swarms of aerial drones have recently been considered for last-mile deliveries in urban logistics or automated construction. At the same time, collaborative transportation of payloads by multiple drones is another important area of recent research. However, efficient coordination algorithms for collaborative transportation of many payloads by many drones remain to be considered. In this work, we formulate the collaborative transportation of payloads by a swarm of drones as a novel, under-capacitated generalization of vehicle routing problems (VRP), which may also be of separate interest. In contrast to standard VRP and capacitated VRP, we must additionally consider waiting times for payloads lifted cooperatively by multiple drones, and the corresponding coordination. Algorithmically, we provide a solution encoding that avoids deadlocks and formulate an appropriate alternating minimization scheme to solve the problem. On the hardware side, we integrate our algorithms with collision avoidance and drone controllers. The approach and the impact of the system integration are successfully verified empirically, both on a swarm of real nano-quadcopters and for large swarms in simulation. Overall, we provide a framework for collaborative transportation with aerial drone swarms, that uses only as many drones as necessary for the transportation of any single payload.