2023/09/09 by Menghao Hu, Tong Zhang, Hu, Menghao +11 · 1 citation
Computer Science · Engineering · #Distributed #Distributed Control Multi-Agent Systems #FOS: Computer and information sciences #FOS: Electrical engineering #Parallel #Robotics and Sensor-Based Localization #Signal Processing (eess.SP) #Systems and Control (eess.SY) #UAV Applications and Optimization #and Cluster Computing (cs.DC) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2309.04730
openalex publication_date 2023/09/09 · openalex created_date 2023/09/13 · openalex updated_date 2026/07/28
Terrestrial robots, i.e., unmanned ground vehicles (UGVs), and aerial robots, i.e., unmanned aerial vehicles (UAVs), operate in separate spaces. To exploit their complementary features (e.g., fields of views, communication links, computing capabilities), a promising paradigm termed integrated robotics network emerges, which provides communications for cooperative UAVs-UGVs applications. However, how to efficiently deploy UAVs and schedule the UAVs-UGVs connections according to different UGV tasks become challenging. In this paper, we propose a sum-rate maximization problem, where UGVs plan their trajectories autonomously and are dynamically associated with UAVs according to their planned trajectories. Although the problem is a NP-hard mixed integer program, a fast polynomial time algorithm using alternating gradient descent and penalty-based binary relaxation, is devised. Simulation results demonstrate the effectiveness of the proposed algorithm.