Abstract
Since microdosing of chemical, biological, radiological, and nuclear (CBRN) contaminants is enough to cause great damage to humans, operating robots are widely used to handle CBRN-related tasks. However, how to improve the automation capabilities of these robots in uneven environments, such as autonomous navigation, is still a huge challenge. Current navigation methods usually set the scene as flat pavement, without considering the situation that the land slope exceeds a certain threshold. In order to explore ways of autonomous navigation in uneven environments, a 3D path planning and navigation method for the tracked robot is proposed in this paper, respecting applicable traversability constraints in uneven terrains. Firstly, a 3D graph-based map is built according to the occupancy map of the uneven environment. A set of spatial points, ensuring collision-avoidance of the robot, is randomly sampled in free space, and a vertex map is generated based on these vertices for robot traversing. Then, regarding the robot’s climbing and obstacle crossing ability as constraints, a path planning algorithm is used to search for the best path based on the Dijkstra algorithm. Finally, a fusion SLAM method based on LiDAR, IMU and RGB-D camera is used to achieve real-time localization, and the pure pursuit algorithm is used for navigation. The simulation results show that the proposed method can provide a safe and effective 3D path for the tracked robot and enable the robot’s autonomous navigation in uneven environments.
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This work is jointly supported by National Natural Science Foundation of China (U1813224).
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He, G., Shi, J., Liu, C., Guo, W., Sheng, X. (2023). Autonomous Navigation of Tracked Robot in Uneven Terrains. In: Yang, H., et al. Intelligent Robotics and Applications. ICIRA 2023. Lecture Notes in Computer Science(), vol 14274. Springer, Singapore. https://doi.org/10.1007/978-981-99-6501-4_7
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DOI: https://doi.org/10.1007/978-981-99-6501-4_7
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