Visual servo algorithm of robot arm simulation for dynamic tracking and grasping application
Health pandemics such as Covid-19 have drastically shifted the world economics and boosted the development of automation technologies in the industries for continuous operation without human intervention. This paper elaborates on an approach to dynamically track and grasp moving objects using a...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2022
|
| Online Access: | http://journalarticle.ukm.my/20340/ http://journalarticle.ukm.my/20340/1/20.pdf |
| _version_ | 1848815078023888896 |
|---|---|
| author | Rishi Arran Suppramaniam, Mohd Hairi Mohd Zaman, Mohd Faisal Ibrahim, Seri Mastura Mustaza, Asraf Mohamed Moubark, |
| author_facet | Rishi Arran Suppramaniam, Mohd Hairi Mohd Zaman, Mohd Faisal Ibrahim, Seri Mastura Mustaza, Asraf Mohamed Moubark, |
| author_sort | Rishi Arran Suppramaniam, |
| building | UKM Institutional Repository |
| collection | Online Access |
| description | Health pandemics such as Covid-19 have drastically shifted the world economics and boosted the development of automation
technologies in the industries for continuous operation without human intervention. This paper elaborates on an approach
to dynamically track and grasp moving objects using a robot arm. The robot arm has an eye-in-hand (EIH) configuration,
where a camera is installed on the robot arm’s end effector. The working principle of the robot arm in this paper is mainly
dependent on the recognition of augmented reality markers, i.e., Aruco markers, placed on the dynamically moving target
object with continuous tracking. Then, the proposed system updates the predicted location for the markers using the Kalman
filter for performing grasping. The proposed approach identifies the Aruco marker on the target object and estimates the
object’s location using previous states, and performs grasping at the exact predicted location. When extracted information
is updated, the vision system also implements a feedback control system for stability and reliability. The proposed approach
is tested using simulation of the dynamic moving object with different speeds and directions. The robot arm with the Kalman
filter can track and grasp the dynamic object at a speed of 0.2m/s with a 100% success rate while obtaining an 80% success
rate at a speed of 0.3m/s. In conclusion, the moving object’s speed is directly proportional to the grasping time until it
reaches the threshold speed for the camera in identifying the Aruco markers. Future works are required to improve the
dynamic visual servo algorithm with motion planning when obstacles are present in the path of robot grasping. |
| first_indexed | 2025-11-15T00:44:15Z |
| format | Article |
| id | oai:generic.eprints.org:20340 |
| institution | Universiti Kebangasaan Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T00:44:15Z |
| publishDate | 2022 |
| publisher | Penerbit Universiti Kebangsaan Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | oai:generic.eprints.org:203402022-11-02T01:20:19Z http://journalarticle.ukm.my/20340/ Visual servo algorithm of robot arm simulation for dynamic tracking and grasping application Rishi Arran Suppramaniam, Mohd Hairi Mohd Zaman, Mohd Faisal Ibrahim, Seri Mastura Mustaza, Asraf Mohamed Moubark, Health pandemics such as Covid-19 have drastically shifted the world economics and boosted the development of automation technologies in the industries for continuous operation without human intervention. This paper elaborates on an approach to dynamically track and grasp moving objects using a robot arm. The robot arm has an eye-in-hand (EIH) configuration, where a camera is installed on the robot arm’s end effector. The working principle of the robot arm in this paper is mainly dependent on the recognition of augmented reality markers, i.e., Aruco markers, placed on the dynamically moving target object with continuous tracking. Then, the proposed system updates the predicted location for the markers using the Kalman filter for performing grasping. The proposed approach identifies the Aruco marker on the target object and estimates the object’s location using previous states, and performs grasping at the exact predicted location. When extracted information is updated, the vision system also implements a feedback control system for stability and reliability. The proposed approach is tested using simulation of the dynamic moving object with different speeds and directions. The robot arm with the Kalman filter can track and grasp the dynamic object at a speed of 0.2m/s with a 100% success rate while obtaining an 80% success rate at a speed of 0.3m/s. In conclusion, the moving object’s speed is directly proportional to the grasping time until it reaches the threshold speed for the camera in identifying the Aruco markers. Future works are required to improve the dynamic visual servo algorithm with motion planning when obstacles are present in the path of robot grasping. Penerbit Universiti Kebangsaan Malaysia 2022 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/20340/1/20.pdf Rishi Arran Suppramaniam, and Mohd Hairi Mohd Zaman, and Mohd Faisal Ibrahim, and Seri Mastura Mustaza, and Asraf Mohamed Moubark, (2022) Visual servo algorithm of robot arm simulation for dynamic tracking and grasping application. Jurnal Kejuruteraan, 34 (4). pp. 729-739. ISSN 0128-0198 https://www.ukm.my/jkukm/volume-3404-2022/ |
| spellingShingle | Rishi Arran Suppramaniam, Mohd Hairi Mohd Zaman, Mohd Faisal Ibrahim, Seri Mastura Mustaza, Asraf Mohamed Moubark, Visual servo algorithm of robot arm simulation for dynamic tracking and grasping application |
| title | Visual servo algorithm of robot arm simulation for dynamic tracking and grasping application |
| title_full | Visual servo algorithm of robot arm simulation for dynamic tracking and grasping application |
| title_fullStr | Visual servo algorithm of robot arm simulation for dynamic tracking and grasping application |
| title_full_unstemmed | Visual servo algorithm of robot arm simulation for dynamic tracking and grasping application |
| title_short | Visual servo algorithm of robot arm simulation for dynamic tracking and grasping application |
| title_sort | visual servo algorithm of robot arm simulation for dynamic tracking and grasping application |
| url | http://journalarticle.ukm.my/20340/ http://journalarticle.ukm.my/20340/ http://journalarticle.ukm.my/20340/1/20.pdf |