考虑平台特性的多层建筑物内履带式无人平台运动规划

doi:10.12382/bgxb.2021.0800

摘要/Abstract

摘要：

针对在多层建筑物内无人平台的自主导航问题，提出一种考虑平台特性的运动规划框架。根据履带式平台的特点，采用零半径转向运动基元方案，并引入维诺路径，提高了全局规划在狭窄环境中的灵活性与安全性。经过分段三次Hermite插值得到平滑的全局路径。基于履带式平台运动模型，在轨迹预测的基础上，利用波阵值来提高局部规划算法在障碍物信息失准情况下的鲁棒性，并结合有限状态机决策模型，实现多楼层间的自主导航任务。对算法进行了仿真与实车实验验证。研究结果表明，新算法能够更好地适应室内环境空间狭窄的特点，同时也证明了在实际环境中的可行性。

关键词: 地面无人平台, 多层建筑物, 运动规划, 自主导航

Abstract:

To solve the navigation problem of the unmanned vehicles in multi-storey buildings, a motion planning framework considering the characteristics of vehicles is proposed. Based on the characteristics of tracked vehicles, the primitive scheme of zero-radius steering is adopted and the Voronoi Path is introduced, which improves the flexibility and safety of the global planner in a narrow environment. Then, the smooth global path is obtained through piecewise cubic Hermite interpolation. Based on model prediction with respecting to the kinematic model of tracked vehicles, the Wavefront Value is introduced to improve the robustness of the local planning algorithm in the case of inaccurate obstacle positioning, and combined with the Finite State Machine to implement the autonomous navigation task between multiple floors. Finally, the simulation and real vehicle experiment are performed. The results show that the proposed algorithm can better adapt to the characteristics of narrow indoor space and also prove its feasibility in the actual environment.

Key words: unmanned ground vehicles, multi-storey buildings, motion plan, autonomous navigation

熊光明, 于全富, 胡秀中, 周子杰, 许佳慧. 考虑平台特性的多层建筑物内履带式无人平台运动规划[J]. 兵工学报, 2023, 44(3): 841-850.

XIONG Guangming, YU Quanfu, HU Xiuzhong, ZHOU Zijie, XU Jiahui. A Motion Planner for Unmanned Tracked Vehicles in Multi-storey Buildings Considering the Characteristics of Vehicles[J]. Acta Armamentarii, 2023, 44(3): 841-850.

图/表 21

图1 有限状态机决策模型示意图

Fig. 1 Schematic diagram of Finite State Machine decision model

图2 同楼层运动规划框架示意图

Fig. 2 Schematic diagram of motion planning framework

图3 多层建筑物环境地图示意图

Fig. 3 Schematic diagram of the multi-storey building hierarchical map

图4 室内环境栅格地图及其维诺图

Fig. 4 Grid map of an indoor environment and its Voronoi map

图5 传统运动基元方案示意图

Fig. 5 Schematic diagram of traditional motion primitives

图6 零半径运动基元方案示意图

Fig. 6 Schematic diagram of zero-radius motion primitives

图7 路径平滑示意图

Fig. 7 Schematic diagram of path smoothing

图8 履带式无人平台运动几何关系示意图

Fig. 8 Schematic diagram of the kinematic geometric relationship of the tracked unmanned platform

图9 轨迹预测示意图

Fig. 9 Schematic diagram of trajectory prediction

图10 波阵值避免局部最小示意图

Fig. 10 Schematic diagram of Wavefront Value avoiding local minimum

图11 仿真环境示意图

Fig. 11 Schematic diagram of the simulation environment

图12 全局规划仿真结果对比图

Fig. 12 Comparison of the global planner’s simulation results

表1 全局规划仿真结果

Table 1 Simulation results of the global planner

算法	扩展基元数量/个	路径长度/m	搜索耗时/ms
传统基元A*	452	18.0	36.8
本文算法	466	12.4	39.2

图13 局部规划仿真对比图(左为遇到障碍物，右为绕过障碍物)

Fig. 13 Comparison of the local planner’s simulation results (left picture shows encountering obstacles, right picture shows bypassing obstacles)

图14 实验无人平台外观

Fig. 14 Appearance of the unmanned platform in the experiment

图15 实验起始点与目标点

Fig. 15 Starting point and target point in the experiment

图16 1层楼内实验结果(左为规划路径，右为实景)

Fig. 16 Experimental results of the first floor (the left is the planned path, and the right is the real scene)

图17 楼梯区域实验结果

Fig. 17 Experimental results of the stair area

图18 转台区域实验结果

Fig. 18 Experimental results of the platform area

图19 第3层楼实验结果(左为规划路径，右为实景)

Fig.19 Experimental results on the third floor (the left is the planned path, right is the real scene)

表2 实车实验结果

Table 2 Results of the experiment

阶段	路径长度/m	实际运动时间/s	平均速度/(m·s^-1)	最大速度/(m·s^-1)
第1层区域	15.2	77	0.20	0.4
楼梯区域	40.6	463	0.10	0.2
第3层区域	23.7	152	0.16	0.4

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