新方法提升机器人复杂地形自主导航能力

Core Insights - The research team at Harbin Institute of Technology (Shenzhen) has made significant advancements in robot path planning, particularly for ground mobile robots navigating rugged terrains, ensuring safe, stable, and efficient autonomous navigation [1][2]. Group 1: Research Achievements - The team developed a hierarchical path planning framework that incorporates terrain analysis and configuration stability estimation, overcoming limitations of traditional methods in both map representation efficiency and stability estimation accuracy [1]. - A novel implicit map representation method based on normal distribution transformation was created for global layer planning, balancing detail in terrain representation with large-scale scene coverage [1]. - The research results were published in the academic journal "IEEE Transactions on Robotics" [1]. Group 2: Methodology - An iterative geometric assessment method was introduced for local layer planning, simulating the robot's contact with the ground under gravity to efficiently estimate configuration stability [2]. - The integration of configuration stability estimation into the path search algorithm allows for the generation of safe and smooth local paths, significantly reducing operational risks such as chassis rollover and bottoming out [2]. - The proposed method is applicable in various scenarios, including large outdoor terrains, multi-layered structures, and complex rubble terrains, and has been validated through simulations and real-world experiments [2].