Applying High-Speed Vision Sensing to an Industrial Robot for High-Performance Position Regulation under Uncertainties
Clicks: 127
ID: 268674
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Popular Article
30.0
/100
127 views
24 readers
AI Quality Assessment
Not analyzed
Readership in this journal
PopularRanked #1,592 of 1,694 articles by views in sensors
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,694 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
It is traditionally difficult to implement fast and accurate position regulation on an industrial robot in the presence of uncertainties. The uncertain factors can be attributed either to the industrial robot itself (e.g., a mismatch of dynamics, mechanical defects such as backlash, etc.) or to the external environment (e.g., calibration errors, misalignment or perturbations of a workpiece, etc.). This paper proposes a systematic approach to implement high-performance position regulation under uncertainties on a general industrial robot (referred to as the main robot) with minimal or no manual teaching. The method is based on a coarse-to-fine strategy that involves configuring an add-on module for the main robot’s end effector. The add-on module consists of a 1000 Hz vision sensor and a high-speed actuator to compensate for accumulated uncertainties. The main robot only focuses on fast and coarse motion, with its trajectories automatically planned by image information from a static low-cost camera. Fast and accurate peg-and-hole alignment in one dimension was implemented as an application scenario by using a commercial parallel-link robot and an add-on compensation module with one degree of freedom (DoF). Experimental results yielded an almost 100% success rate for fast peg-in-hole manipulation (with regulation accuracy at about 0.1 mm) when the workpiece was randomly placed.
| Reference Key |
huang2016sensorsapplying
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Shouren Huang;Niklas Bergström;Yuji Yamakawa;Taku Senoo;Masatoshi Ishikawa;Huang, Shouren;Bergström, Niklas;Yamakawa, Yuji;Senoo, Taku;Ishikawa, Masatoshi; |
| Journal | sensors |
| Year | 2016 |
| DOI |
10.3390/s16081195
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.