Predictive control of an efficient human following robot using Kinect sensor

Shin Nyeong Heo, Jang Myung Lee

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

This paper proposes a predictive control for an efficient human following robot using Kinect sensor. Especially, this research is focused on detecting of foot-end-point and foot-vector instead of human body which can be occluded easily by the obstacles. Recognition of the foot-end-point by the Kinect sensor is reliable since the two feet images can be utilized, which increases the detection possibility of the human motion. Depth image features and a decision tree have been utilized to estimate the foot endpoint precisely. A tracking point average algorithm is also adopted in this research to estimate the location of foot accurately. Using the continuous locations of foot, the human motion trajectory is estimated to guide the mobile robot along a smooth path to the human. It is verified through the experiments that detecting foot-end-point is more reliable and efficient than detecting the human body. Finally, the tracking performance of the mobile robot is demonstrated with a human motion along an 'L' shape course.

Original languageKorean
Pages (from-to)957-963
Number of pages7
JournalJournal of Institute of Control, Robotics and Systems
Volume20
Issue number9
DOIs
Publication statusPublished - 2014
Externally publishedYes

Keywords

  • Foot vector
  • Human following robot
  • Kinect sensor
  • Tracking performance

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Applied Mathematics

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