Flexible Computer Vision based Sample Switching System using a Robotic Arm
(2024)Department of Automatic Control
- Abstract
- This thesis presents the development of a computer vision based robotic system for flexible sample switching at the European Spallation Source (ESS). At ESS, samples will be placed in the neutron beam by the instruments. These environments will be exposed to radiation, making direct access to the samples difficult for personnel. To maximize scientific output, it is also desirable to minimize the downtime of the neutron beam. These factors make an automated solution for sample switching highly desirable. Traditional robotic systems often lack the adaptability needed to perform in settings that are subject to change. Consequently, it is hard to develop robotic systems that are general enough to be independent of a specific robotic arm and... (More)
- This thesis presents the development of a computer vision based robotic system for flexible sample switching at the European Spallation Source (ESS). At ESS, samples will be placed in the neutron beam by the instruments. These environments will be exposed to radiation, making direct access to the samples difficult for personnel. To maximize scientific output, it is also desirable to minimize the downtime of the neutron beam. These factors make an automated solution for sample switching highly desirable. Traditional robotic systems often lack the adaptability needed to perform in settings that are subject to change. Consequently, it is hard to develop robotic systems that are general enough to be independent of a specific robotic arm and the environment, using the traditional approach. This project addresses these limitations by creating a robotic system capable of operating autonomously in a dynamic environment.
The system integrates several components: a Stäubli TX60 industrial robot, an Intel RealSense D435if depth camera, and custom 3D-printed sample handles with ArUco markers for identification and pose estimation. ROS is used for control and perception, and EPICS drivers is developed for integration with ESS’s control system.
The results demonstrate the feasibility of integrating autonomous robotic systems into complex research environments, showing promise in improving operational functionality in sample handling at ESS. Future work will focus on enhancing system robustness, upgrading hardware, expanding functionality, and further integration with ESS’s control systems.
Overall, this thesis contributes to the greater field of robotics by providing a case study of a versatile and adaptable robotic system, highlighting challenges and solutions in developing autonomous systems for scientific research. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9171814
- author
- Andersson, Anthon and Håkansson, Anton
- supervisor
- organization
- year
- 2024
- type
- H3 - Professional qualifications (4 Years - )
- subject
- report number
- TFRT-6247
- other publication id
- 0280-5316
- language
- English
- id
- 9171814
- date added to LUP
- 2024-08-15 14:07:30
- date last changed
- 2024-08-15 14:07:30
@misc{9171814, abstract = {{This thesis presents the development of a computer vision based robotic system for flexible sample switching at the European Spallation Source (ESS). At ESS, samples will be placed in the neutron beam by the instruments. These environments will be exposed to radiation, making direct access to the samples difficult for personnel. To maximize scientific output, it is also desirable to minimize the downtime of the neutron beam. These factors make an automated solution for sample switching highly desirable. Traditional robotic systems often lack the adaptability needed to perform in settings that are subject to change. Consequently, it is hard to develop robotic systems that are general enough to be independent of a specific robotic arm and the environment, using the traditional approach. This project addresses these limitations by creating a robotic system capable of operating autonomously in a dynamic environment. The system integrates several components: a Stäubli TX60 industrial robot, an Intel RealSense D435if depth camera, and custom 3D-printed sample handles with ArUco markers for identification and pose estimation. ROS is used for control and perception, and EPICS drivers is developed for integration with ESS’s control system. The results demonstrate the feasibility of integrating autonomous robotic systems into complex research environments, showing promise in improving operational functionality in sample handling at ESS. Future work will focus on enhancing system robustness, upgrading hardware, expanding functionality, and further integration with ESS’s control systems. Overall, this thesis contributes to the greater field of robotics by providing a case study of a versatile and adaptable robotic system, highlighting challenges and solutions in developing autonomous systems for scientific research.}}, author = {{Andersson, Anthon and Håkansson, Anton}}, language = {{eng}}, note = {{Student Paper}}, title = {{Flexible Computer Vision based Sample Switching System using a Robotic Arm}}, year = {{2024}}, }