Research on Path Planning of Mobile Equipment in Dynamic Confined Space of Underground Roadway
Received date: 2022-10-18
Revised date: 2023-01-11
Online published: 2023-04-27
With the rapid development of unmanned driving technology，the driverless vehicles on the road have been widely used，which has laid a solid foundation for the fully unmanned mine.Especially for un-derground operation equipment，the roadway environment has the characteristics of closedness，irregular driving area，and difficulty in environmental perception，which makes the mobile equipment of underground manual driving inefficient and frequent accidents.So in a chaotic，irregular and dynamic environment，a safe and efficient autonomous navigation system is essential.The traditional autonomous navigation of underground mobile equipment mainly relies on pre-established static maps to make global path planning，then directly hands over the global path to control model，which makes it impossible to update the map in time when encountering sudden obstacles，resulting in oscillating trajectories and crooked paths.In order to solve the above problems，this article proposed the improved TEB （Time Elastic Band） local path planning to quickly update the path by combining global planning and local planning on the basis of mapping and navigation.In order to adapt the underground roadway environment， add target point constraints，urgency constraints，end smoothing constraints and energy consumption constraints，the nonlinear optimization problem can be iteratively solved through the G2O graph optimization framework to obtain a suboptimal solution that meets the requirements，the programming speed is within 100 ms.By simulating the dual-lane collision-free，dual-lane oncoming traffic，dynamic crossing scene，according to the principle of underground driving，the improved TEB algorithm produces a more feasible trajectory，which effectively shortens the path length，reduces the number of turns and stops，especially the path smoothness at the corner，and the operating efficiency is higher than the traditional TEB path planning algorithm.The average path generation value before the improvement was 23.09，and the average path generation value after the improvement was 10.19，which decreased the overall generation value by 55.87%.Finally，the unmanned vehicle experimental platform is used to build random obstacles in the underground roadway scene according to the 9∶1 scale，and the feasibility of the algorithm is verified in the dynamic cross environment，which can satisfy the safe and efficient driving of underground mobile equipment in the roadway.
Zhuo LIU , Mingtao JIA , Liguan WANG . Research on Path Planning of Mobile Equipment in Dynamic Confined Space of Underground Roadway[J]. Gold Science and Technology, 2023 , 31(2) : 302 -312 . DOI: 10.11872/j.issn.1005-2518.2023.02.149
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