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 language | Korean |
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Pages (from-to) | 957-963 |
Number of pages | 7 |
Journal | Journal of Institute of Control, Robotics and Systems |
Volume | 20 |
Issue number | 9 |
DOIs | |
Publication status | Published - 2014 |
Externally published | Yes |
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Keywords
- Foot vector
- Human following robot
- Kinect sensor
- Tracking performance
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Applied Mathematics
Cite this
Predictive control of an efficient human following robot using Kinect sensor. / Heo, Shin Nyeong; Lee, Jang Myung.
In: Journal of Institute of Control, Robotics and Systems, Vol. 20, No. 9, 2014, p. 957-963.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Predictive control of an efficient human following robot using Kinect sensor
AU - Heo, Shin Nyeong
AU - Lee, Jang Myung
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Foot vector
KW - Human following robot
KW - Kinect sensor
KW - Tracking performance
UR - http://www.scopus.com/inward/record.url?scp=84922976239&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84922976239&partnerID=8YFLogxK
U2 - 10.5302/J.ICROS.2014.14.0019
DO - 10.5302/J.ICROS.2014.14.0019
M3 - Article
AN - SCOPUS:84922976239
VL - 20
SP - 957
EP - 963
JO - Journal of Institute of Control, Robotics and Systems
JF - Journal of Institute of Control, Robotics and Systems
SN - 1976-5622
IS - 9
ER -