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Evaluating the Energy Consumption of Path Planning Algorithms: A Comparative Study of A*, Dijkstra and Probabilistic Roadmap

  • Mingyu Wu,
  • Haoyu Jiang,
  • Che Fai Yeong,
  • Eileen Lee Ming Su,
  • Chenguang Yang,
  • William Holderbaum

摘要

This study evaluates the energy efficiency of three path-planning algorithms—A*, Dijkstra, and probabilistic roadmap (PRM)—in warehouse environments, using computer simulations and real-world tests with TurtleBot3 Waffle Pi. The research challenges conventional beliefs by revealing a non-linear relationship between robot velocity and energy consumption. A* is found to be more energy-efficient, especially in complex settings. The study suggests that energy efficiency should be a key consideration in future algorithm design and has essential implications for robots operating in various environments.