Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Yeo Jung Yoon"'
Publikováno v:
Journal of Manufacturing Science & Engineering; Feb2024, Vol. 146 Issue 2, p1-11, 11p
Autor:
Neel Dhanaraj, Yeo Jung Yoon, Rishi Malhan, Prahar M. Bhatt, Shantanu Thakar, Satyandra K. Gupta
Publikováno v:
Procedia Computer Science. 200:1528-1539
Autor:
Yeo Jung Yoon, Satyandra K. Gupta
Publikováno v:
Volume 2: 42nd Computers and Information in Engineering Conference (CIE).
Learning the right process parameters is essential to efficiently and safely execute tasks in automated manufacturing applications. When there is a risk of damaging the object, conducting experiments on sacrificial objects is a good option to explore
Autor:
Shantanu Thakar, Srivatsan Srinivasan, Sarah Al-Hussaini, Prahar M. Bhatt, Pradeep Rajendran, Yeo Jung Yoon, Neel Dhanaraj, Rishi K. Malhan, Matthias Schmid, Venkat N. Krovi, Satyandra K. Gupta
Publikováno v:
Journal of Mechanisms and Robotics. 15
Mobile manipulators that combine base mobility with the dexterity of an articulated manipulator have gained popularity in numerous applications ranging from manufacturing and infrastructure inspection to domestic service. Deployments span a range of
Autor:
Ashish Kulkarni, Yeo Jung Yoon, Rishi K. Malhan, Prahar M. Bhatt, Satyandra K. Gupta, Brual C. Shah
Publikováno v:
Journal of Computing and Information Science in Engineering. 22
Conventional material extrusion additive manufacturing (AM) processes require the user to make a trade-off between surface quality and build time of the part. A large bead filament deposition can speed up the build process; however, it leads to surfa
Autor:
Yeo Jung Yoon, Satyandra K. Gupta
Publikováno v:
Volume 2: 41st Computers and Information in Engineering Conference (CIE).
To execute non-repetitive tasks, robots need to learn on the tasks to improve task performance. The performance model cannot be built in advance for such non-repetitive tasks. The robot can execute a small portion of the task with certain process par
Autor:
Rishi K. Malhan, Yeo Jung Yoon, Prahar M. Bhatt, Pradeep Rajendran, Brual C. Shah, Satyandra K. Gupta, Shantanu Thakar
Publikováno v:
Journal of Computing and Information Science in Engineering. 21
Automatically detecting surface defects from images is an essential capability in manufacturing applications. Traditional image processing techniques are useful in solving a specific class of problems. However, these techniques do not handle noise, v
Publikováno v:
Volume 1: Additive Manufacturing; Advanced Materials Manufacturing; Biomanufacturing; Life Cycle Engineering; Manufacturing Equipment and Automation.
By attaching a material extrusion system to a robotic arm, we can deposit materials onto complex surfaces. Robotic manipulators can also maximize the task utility by performing other tasks such as assembly or surface polishing when they are not in us