Abstract
This paper proposes a framework for visualizing comprehensive work tendency using a frequency plot map of the end-point of a manipulator as a fundamental study of work analysis using long-term data for human-operated work machines. A visualization system requires high generality and commonality to enable to extract various characteristics to be extracted on an arbitrary time scale independently of the work machine specifications, work contents and environment, and machine operator. The proposed framework meets this requirement by first creating a two-dimensional end-point plot map with its origin fixed at the yaw joint of the manipulator to deal with arbitrary usage conditions. It then extracts arbitrary characteristics by using hierarchical feature extraction filters, including binary, quantity, and advanced filters, defined by three kinds of essential data: operation, movement, and load. Finally, it quantifies the filtered map by gridding and normalization to visually grasp its frequency distribution. Two experiments in which the work environments and completion time differed were conducted using an instrumented hydraulic arm. Results indicated that the comprehensive work tendency revealed by using the proposed framework corresponds to the actual work results independently of the various conditions.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - IEEE International Conference on Robotics and Automation |
| Pages | 760-765 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 2013 |
| Event | 2013 IEEE International Conference on Robotics and Automation, ICRA 2013 - Karlsruhe Duration: 2013 May 6 → 2013 May 10 |
Other
| Other | 2013 IEEE International Conference on Robotics and Automation, ICRA 2013 |
|---|---|
| City | Karlsruhe |
| Period | 13/5/6 → 13/5/10 |
Fingerprint
ASJC Scopus subject areas
- Software
- Artificial Intelligence
- Control and Systems Engineering
- Electrical and Electronic Engineering
Cite this
Visualization of comprehensive work tendency using end-point frequency map for human-operated work machines. / Kamezaki, Mitsuhiro; Iwata, Hiroyasu; Sugano, Shigeki.
Proceedings - IEEE International Conference on Robotics and Automation. 2013. p. 760-765 6630658.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Visualization of comprehensive work tendency using end-point frequency map for human-operated work machines
AU - Kamezaki, Mitsuhiro
AU - Iwata, Hiroyasu
AU - Sugano, Shigeki
PY - 2013
Y1 - 2013
N2 - This paper proposes a framework for visualizing comprehensive work tendency using a frequency plot map of the end-point of a manipulator as a fundamental study of work analysis using long-term data for human-operated work machines. A visualization system requires high generality and commonality to enable to extract various characteristics to be extracted on an arbitrary time scale independently of the work machine specifications, work contents and environment, and machine operator. The proposed framework meets this requirement by first creating a two-dimensional end-point plot map with its origin fixed at the yaw joint of the manipulator to deal with arbitrary usage conditions. It then extracts arbitrary characteristics by using hierarchical feature extraction filters, including binary, quantity, and advanced filters, defined by three kinds of essential data: operation, movement, and load. Finally, it quantifies the filtered map by gridding and normalization to visually grasp its frequency distribution. Two experiments in which the work environments and completion time differed were conducted using an instrumented hydraulic arm. Results indicated that the comprehensive work tendency revealed by using the proposed framework corresponds to the actual work results independently of the various conditions.
AB - This paper proposes a framework for visualizing comprehensive work tendency using a frequency plot map of the end-point of a manipulator as a fundamental study of work analysis using long-term data for human-operated work machines. A visualization system requires high generality and commonality to enable to extract various characteristics to be extracted on an arbitrary time scale independently of the work machine specifications, work contents and environment, and machine operator. The proposed framework meets this requirement by first creating a two-dimensional end-point plot map with its origin fixed at the yaw joint of the manipulator to deal with arbitrary usage conditions. It then extracts arbitrary characteristics by using hierarchical feature extraction filters, including binary, quantity, and advanced filters, defined by three kinds of essential data: operation, movement, and load. Finally, it quantifies the filtered map by gridding and normalization to visually grasp its frequency distribution. Two experiments in which the work environments and completion time differed were conducted using an instrumented hydraulic arm. Results indicated that the comprehensive work tendency revealed by using the proposed framework corresponds to the actual work results independently of the various conditions.
UR - http://www.scopus.com/inward/record.url?scp=84887272635&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84887272635&partnerID=8YFLogxK
U2 - 10.1109/ICRA.2013.6630658
DO - 10.1109/ICRA.2013.6630658
M3 - Conference contribution
AN - SCOPUS:84887272635
SN - 9781467356411
SP - 760
EP - 765
BT - Proceedings - IEEE International Conference on Robotics and Automation
ER -