Volume 30 Issue 6
Nov.  2021
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GONG Linxi, CAI Yunfei. Human Following for Outdoor Mobile Robots Based on Point-Cloud's Appearance Model[J]. Chinese Journal of Electronics, 2021, 30(6): 1087-1095. doi: 10.1049/cje.2021.07.017
Citation: GONG Linxi, CAI Yunfei. Human Following for Outdoor Mobile Robots Based on Point-Cloud's Appearance Model[J]. Chinese Journal of Electronics, 2021, 30(6): 1087-1095. doi: 10.1049/cje.2021.07.017

Human Following for Outdoor Mobile Robots Based on Point-Cloud's Appearance Model

doi: 10.1049/cje.2021.07.017
Funds:

This work is supported by the Fund for Technical Field of the Foundation Strengthening Programme (No.2019-JCJQ-JJ-355).

  • Received Date: 2020-10-23
  • Rev Recd Date: 2021-01-28
  • Available Online: 2021-09-23
  • Publish Date: 2021-11-05
  • In this paper, we propose a point-cloudbased algorithm for human-following robots to detect and follow the target person in a complex outdoor environment. Specifically, we exploit AdaBoost to train a binary classifier in a designed feature space based on sparse point-cloud to distinguish the target person from other objects. Then a particle filter is applied to continuously track the target's position. Motivated by the interference of obstacles in long-distance human-following scenarios, a motion plan algorithm based on vector field histogram is adopted. Experiments are carried out both on the dataset we collected and in real application scenarios. The results show that our algorithm has the ability of real-time target detection and tracking, and is robust to deal with complex situations in outdoor environments.
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