基于A*和TEB融合的行人感知无碰跟随方法

doi:10.7527/S1000-6893.2020.24909

电子电气工程与控制

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基于A^*和TEB融合的行人感知无碰跟随方法

庞磊^1,2, 曹志强^1,2, 喻俊志^1,3

1. 中国科学院自动化研究所复杂系统管理与控制国家重点实验室, 北京 100190;
2. 中国科学院大学人工智能学院, 北京 100049;
3. 北京大学工学院先进制造与机器人系, 北京 100871

收稿日期:2020-10-21 修回日期:2020-11-12 发布日期:2020-11-27
通讯作者: 喻俊志 E-mail:junzhi.yu@ia.ac.cn
基金资助:
国家自然科学基金（61633020，61633017，61725305，61836015）

A pedestrian-aware collision-free following approach for mobile robots based on A^* and TEB

PANG Lei^1,2, CAO Zhiqiang^1,2, YU Junzhi^1,3

1. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China;
2. School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China;
3. Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing 100871, China

Received:2020-10-21 Revised:2020-11-12 Published:2020-11-27
Supported by:
National Natural Science Foundation of China (61633020, 61633017, 61725305, 61836015)

摘要/Abstract

摘要： 移动机器人通过跟随一个指定行人实现导航是一种便捷的方式。针对行人跟随中的机器人跟随和避障问题，提出了一种基于路径规划的无碰跟随方法。该方法结合激光点云分割提供的非行人障碍信息生成静态障碍代价地图，并根据3D行人定位结果，利用基于无迹卡尔曼滤波器（Unscented Kalman Filter，UKF）和最近邻联合概率数据关联（Nearest Near Joint Probabilistic Data Association，NN-JPDA）的多行人跟踪器估计干扰行人运动状态，进而生成动态行人代价地图。在此基础上，基于A^*的全局规划器结合静态障碍代价地图输出指向目标行人的全局路径，而基于时间弹性带（TEB）算法的局部规划器也将动态行人代价地图纳入考虑范围以规划优化的局部路径，这能够帮助机器人实现行人感知的避障且跟随全局路径。通过低频全局规划与高频局部规划结合的方式实现对目标行人安全无碰的跟随。实验验证了所提方法的有效性。

关键词: 导航, 行人跟随, 路径规划, 避障, 运动状态估计, 无碰跟随

Abstract: Navigation by following a specified leader is a convenient way for mobile robots. To solve the problem of robot’s following with obstacle avoidance, a collision-free following approach based on path planning is proposed. The static obstacle cost map is generated according to the results of the point cloud segmentation. Multiple disturbing pedestrians are tracked based on the Unscented Kalman Filter (UKF) and Nearest Near Joint Probabilistic Data Association (NN-JPDA) to estimate their motion states, and then the dynamic pedestrian cost map is generated. On this basis, the A^*-based global planner plans a global path with the static obstacle cost map, whereas the local planner implemented with Timed-Elastic-Band (TEB) algorithm also takes the dynamic pedestrian cost map into account to plan an optimized local path. This local path tends to follow the global path and helps the mobile robot achieve pedestrian-aware obstacle avoidance. By combining low-frequency global planning with high-frequency local planning, the mobile robot realizes a safe and collision-free person following. The effectiveness of the proposed approach is validated by experiments.

Key words: navigation, person following, path planning, obstacle avoidance, motion estimation, collision-free following

中图分类号:

V249.32

庞磊, 曹志强, 喻俊志. 基于A^*和TEB融合的行人感知无碰跟随方法[J]. 航空学报, 2021, 42(4): 524909-524909.

PANG Lei, CAO Zhiqiang, YU Junzhi. A pedestrian-aware collision-free following approach for mobile robots based on A^* and TEB[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2021, 42(4): 524909-524909.

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基于A^*和TEB融合的行人感知无碰跟随方法

A pedestrian-aware collision-free following approach for mobile robots based on A^* and TEB

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基于A*和TEB融合的行人感知无碰跟随方法

A pedestrian-aware collision-free following approach for mobile robots based on A* and TEB

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基于A^*和TEB融合的行人感知无碰跟随方法

A pedestrian-aware collision-free following approach for mobile robots based on A^* and TEB