Human-following task without a prior map

Zhiqiang Zhou, Yong Fu, Wei Wu
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Abstract

Purpose

The human-following task is a fundamental function in human–robot collaboration. It requires a robot to recognize and locate a target person, plan a path and avoid obstacles. To enhance the applicability of the human-following task in various scenarios, it should not rely on a prior map. This paper aims to introduce a human-following method that meets these requirements.

Design/methodology/approach

For the identification and localization of the target person (ILTP), this paper proposes an approach that integrates data from a camera, a light detection and ranging (LiDAR) and a ultra-wideband (UWB) anchor. For path planning and obstacle avoidance, a modified timed-elastic-bands (TEB) algorithm is introduced.

Findings

Compared to the UWB-only method, where only UWB is used to locate the target person, the proposed ILTP method in this paper reduces the localization error by 41.82%. Experimental results demonstrate the effectiveness of the ILTP and the modified TEB method under various challenging conditions. Such as crowded environments, multiple obstacles, the target person being occluded and the target person moving out of the robot’s field of view. The complete experimental videos are available for viewing on https://youtu.be/ZKbrNE1sePM.

Originality/value

This paper offers a novel solution for human-following tasks. The proposed ILTP method can recognize the target person among multiple individuals, determine whether the target person is lost and publish the target person’s position at a frequency of 20 Hz. The modified TEB algorithm does not rely on a prior map. It can plan paths and avoid obstacles effectively.

无先验地图的人类跟踪任务
目的 人类跟随任务是人机协作中的一项基本功能。它要求机器人识别和定位目标人物,规划路径并避开障碍物。为了提高人机跟随任务在各种场景中的适用性,它不应依赖于先验地图。对于目标人物的识别和定位(ILTP),本文提出了一种集成了摄像头、光探测和测距(LiDAR)以及超宽带(UWB)锚的方法。与仅使用 UWB 定位目标人物的方法相比,本文提出的 ILTP 方法将定位误差降低了 41.82%。实验结果证明了 ILTP 和改进的 TEB 方法在各种挑战条件下的有效性。例如拥挤的环境、多重障碍物、目标人物被遮挡以及目标人物移出机器人视野等。完整的实验视频可在 https://youtu.be/ZKbrNE1sePM.Originality/valueThis 上观看,本文为人类跟随任务提供了一种新颖的解决方案。所提出的 ILTP 方法可以在多个个体中识别目标人物,判断目标人物是否丢失,并以 20 Hz 的频率发布目标人物的位置。改进的 TEB 算法不依赖于先验地图。它可以有效地规划路径和避开障碍物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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