TeleopLab: Accessible and Intuitive Teleoperation of a Robotic Manipulator for Remote Labs
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866908522231365632 |
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| author | Chen, Ziling Yoon, Yeo Jung Bautista-Montesano, Rolando Zhao, Zhen Mandlekar, Ajay Liu, John |
| author_facet | Chen, Ziling Yoon, Yeo Jung Bautista-Montesano, Rolando Zhao, Zhen Mandlekar, Ajay Liu, John |
| contents | Teleoperation offers a promising solution for enabling hands-on learning in remote education, particularly in environments requiring interaction with real-world equipment. However, such remote experiences can be costly or non-intuitive. To address these challenges, we present TeleopLab, a mobile device teleoperation system that allows students to control a robotic arm and operate lab equipment. TeleopLab comprises a robotic arm, an adaptive gripper, cameras, lab equipment for a diverse range of applications, a user interface accessible through smartphones, and video call software. We conducted a user study, focusing on task performance, students' perspectives toward the system, usability, and workload assessment. Our results demonstrate a 46.1% reduction in task completion time as users gained familiarity with the system. Quantitative feedback highlighted improvements in students' perspectives after using the system, while NASA TLX and SUS assessments indicated a manageable workload of 38.2 and a positive usability of 73.8. TeleopLab successfully bridges the gap between physical labs and remote education, offering a scalable and effective platform for remote STEM learning. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_05547 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | TeleopLab: Accessible and Intuitive Teleoperation of a Robotic Manipulator for Remote Labs Chen, Ziling Yoon, Yeo Jung Bautista-Montesano, Rolando Zhao, Zhen Mandlekar, Ajay Liu, John Robotics Human-Computer Interaction Teleoperation offers a promising solution for enabling hands-on learning in remote education, particularly in environments requiring interaction with real-world equipment. However, such remote experiences can be costly or non-intuitive. To address these challenges, we present TeleopLab, a mobile device teleoperation system that allows students to control a robotic arm and operate lab equipment. TeleopLab comprises a robotic arm, an adaptive gripper, cameras, lab equipment for a diverse range of applications, a user interface accessible through smartphones, and video call software. We conducted a user study, focusing on task performance, students' perspectives toward the system, usability, and workload assessment. Our results demonstrate a 46.1% reduction in task completion time as users gained familiarity with the system. Quantitative feedback highlighted improvements in students' perspectives after using the system, while NASA TLX and SUS assessments indicated a manageable workload of 38.2 and a positive usability of 73.8. TeleopLab successfully bridges the gap between physical labs and remote education, offering a scalable and effective platform for remote STEM learning. |
| title | TeleopLab: Accessible and Intuitive Teleoperation of a Robotic Manipulator for Remote Labs |
| topic | Robotics Human-Computer Interaction |
| url | https://arxiv.org/abs/2509.05547 |