Integrated Robotics Networks with Co-optimization of Drone Placement and Air-Ground Communications

TL;DR

This paper introduces an integrated robotics network that optimizes drone placement and air-ground communication scheduling to enhance cooperative UAV-UGV operations, addressing deployment and connection challenges.

Contribution

It proposes a novel sum-rate maximization framework with a polynomial-time algorithm for joint UAV placement and UGV trajectory planning.

Findings

The algorithm effectively maximizes communication sum-rate.

Simulation results validate the approach's efficiency.

The method handles NP-hard optimization with practical performance.

Abstract

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.