“FOLO”: A Vision-Based Human-Following Robot

DOI

10.2991/amcce-18.2018.40How to use a DOI?

Keywords

Human-following, Learning Detection, Autonomous navigation.

Abstract

The main challenge in following robot is solving the real-time user localization problem. In this paper we introduce our solution for it together with our whole robot system called “FOLO”. Using extra-tool (such as Bluetooth) may cause inconvenience in interaction; 3D detector plus tracker ID approaches are at risks of computing consume and ROI flash; Approaches based on 2D appearance have challenges on appearance change, re-detecting and complex background. We present a 2D-appearance approach on “FOLO” which can work overcome above issues. Our approach utilizes consensus of corresponding method to track, and then, updates features by supervised learning into classifier cascade to against challenges of re-detecting and complex background. Moreover, we give pre-processing procedure on each frame to sharpen edges on image to enhance quality of tracking and use adaptive background to overcome challenge of complex background. This paper illustrates that our tracking approach can work against common challenges of tracking in our own designed experiments, has a rapid speed over 25 fps and can achieve state-of-the-art results. We use two-layer-PID method to control “FOLO” for a long-term task which allows “FOLO” succeeding to follow user in office environment.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Evan Chen
PY  - 2018/05
DA  - 2018/05
TI  - “FOLO”: A Vision-Based Human-Following Robot
BT  - Proceedings of the 2018 3rd International Conference on Automation, Mechanical Control and Computational Engineering (AMCCE 2018)
PB  - Atlantis Press
SP  - 224
EP  - 232
SN  - 2352-5401
UR  - https://doi.org/10.2991/amcce-18.2018.40
DO  - 10.2991/amcce-18.2018.40
ID  - Chen2018/05
ER  -