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.
@article{arxiv.2309.04730,
title = {Integrated Robotics Networks with Co-optimization of Drone Placement and Air-Ground Communications},
author = {Menghao Hu and Tong Zhang and Shuai Wang and Guoliang Li and Yingyang Chen and Qiang Li and Gaojie Chen},
journal= {arXiv preprint arXiv:2309.04730},
year = {2023}
}