Wireless Channel Modeling for Viewpoint and Trajectory Planning in Aerial Coverage Exploration
Kai Hu, Longhao Zou, Mingcheng Luo, Jun Jiang, Rui Li · 2025
The rapid advancement of wireless communication technologies has improved the connectivity and operational capabilities of robotic vehicles, enabling their use in applications such as urban monitoring, infrastructure inspection, and disaster response. However, these systems still face key challenges, including limited computational resources, unstable connectivity, and inefficient energy use. Existing coverage exploration methods often neglect real-world wireless communication constraints, relying on idealized conditions or lacking integration of physical and communication factors, which limits their practical effectiveness. This paper proposes a framework that leverages wireless channel modeling for viewpoint and trajectory planning. First, the framework employs ray tracing-based propagation modeling and wireless channel mapping to achieve precise wireless link-level modeling. Next, it integrates a multi-objective viewpoint optimization strategy to balance spatial coverage and communication reliability. Finally, it incorporates a communication-driven trajectory planning method to adapt to realistic wireless conditions. The experimental results demonstrate the effectiveness of the proposed method in achieving reliable coverage exploration and robust wireless communication. This work enhances the resilience and efficiency of robotic operations in urban environments by enabling robust path planning, navigation, and target tracking through wireless communication, contributing to broader sustainable development goals.