Mobility Prediction of a Novel Unmanned Robot over Large off-Road Regions
Chen Hua, Jie Wang, Rengui Bai, Xiaokun Zheng · 2022 IEEE International Conference on Mechatronics and Automation (ICMA) · 2022
Because of the complex terrain structure in the off road environments, and the lack of mobility of traditional multi-wheeled tracked robots, a novel $6 \times 6$ wheeled-track unmanned robot (6-WTU) is designed in this study. we describes a large spatial region mobility prediction method for the robot (>5×5km2). For more accurate and efficient prediction of the robot’s mobility in off-road environments. We used the Ordinary Kriging method to refine the digital elevation map (DEM), however, before the interpolation, we compared three sampling methods, and selected the optimal sampling method by comparing the semi-variogram to reduce the calculation of the interpolation. After the reconstruction of the DEM. The GO/NOGO map was generated by combining the terrain features and the kinematic limits of the robot. To further demonstrate the validity of the mobility prediction proposed in this paper, the path planning algorithms of two strategies were used, and the effectiveness of the mobility prediction was verified by simulation experiments.