A Survey of Path Planning Algorithms for Inspection Robots - Wu, Chuangren (International Journal of Computer Science and Information Technology, 2025)
Against the backdrop of inspection robots being widely applied in complex dynamic scenarios such as industrial automation and intelligent services, this paper systematically reviews three mainstream path planning algorithms—traditional algorithms (A*, Dijkstra, and their improved variants), sampling-based algorithms (PRM, RRT*, and their variants), and intelligent optimization algorithms (genetic algorithm, particle swarm optimization, ant colony optimization, and their enhancements)—by synthesizing domestic and international research. It examines their core principles, advantages, limitations, and applicable scenarios, with a focus on cutting-edge trends such as algorithm integration, multi-sensor perception synergy, and multi-objective optimization. The review provides a clear framework for understanding algorithm applicability and selection across diverse scenarios, and aims to offer theoretical references for developing efficient, robust path planning technologies tailored to complex dynamic environments in future inspection robots.