Towards Real-Time Generation of Delay-Compensated Video Feeds for Outdoor Mobile Robot Teleoperation
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arXiv
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| Main Authors: | , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866917924116103168 |
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| author | Chakraborty, Neeloy Fang, Yixiao Schreiber, Andre Ji, Tianchen Huang, Zhe Mihigo, Aganze Wall, Cassidy Almana, Abdulrahman Driggs-Campbell, Katherine |
| author_facet | Chakraborty, Neeloy Fang, Yixiao Schreiber, Andre Ji, Tianchen Huang, Zhe Mihigo, Aganze Wall, Cassidy Almana, Abdulrahman Driggs-Campbell, Katherine |
| contents | Teleoperation is an important technology to enable supervisors to control agricultural robots remotely. However, environmental factors in dense crop rows and limitations in network infrastructure hinder the reliability of data streamed to teleoperators. These issues result in delayed and variable frame rate video feeds that often deviate significantly from the robot's actual viewpoint. We propose a modular learning-based vision pipeline to generate delay-compensated images in real-time for supervisors. Our extensive offline evaluations demonstrate that our method generates more accurate images compared to state-of-the-art approaches in our setting. Additionally, ours is one of the few works to evaluate a delay-compensation method in outdoor field environments with complex terrain on data from a real robot in real-time. Resulting videos and code are provided at https://sites.google.com/illinois.edu/comp-teleop. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_09921 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards Real-Time Generation of Delay-Compensated Video Feeds for Outdoor Mobile Robot Teleoperation Chakraborty, Neeloy Fang, Yixiao Schreiber, Andre Ji, Tianchen Huang, Zhe Mihigo, Aganze Wall, Cassidy Almana, Abdulrahman Driggs-Campbell, Katherine Robotics Computer Vision and Pattern Recognition Teleoperation is an important technology to enable supervisors to control agricultural robots remotely. However, environmental factors in dense crop rows and limitations in network infrastructure hinder the reliability of data streamed to teleoperators. These issues result in delayed and variable frame rate video feeds that often deviate significantly from the robot's actual viewpoint. We propose a modular learning-based vision pipeline to generate delay-compensated images in real-time for supervisors. Our extensive offline evaluations demonstrate that our method generates more accurate images compared to state-of-the-art approaches in our setting. Additionally, ours is one of the few works to evaluate a delay-compensation method in outdoor field environments with complex terrain on data from a real robot in real-time. Resulting videos and code are provided at https://sites.google.com/illinois.edu/comp-teleop. |
| title | Towards Real-Time Generation of Delay-Compensated Video Feeds for Outdoor Mobile Robot Teleoperation |
| topic | Robotics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2409.09921 |