TeleMotion: A Realtime Humanoid Teleoperation System with Motion Capture
Authors: Gan, J., Guo, S., Li, Z., Shi, X.
Journal: Lecture Notes in Computer Science
Publication Date: 01/01/2025
Volume: 15461 LNCS
Pages: 31-45
eISSN: 1611-3349
ISSN: 0302-9743
DOI: 10.1007/978-981-96-3679-2_3
Abstract:Teleoperation serves as a vital means of interaction between humans and robots, aiming to enable robots to move in accordance with human intentions. An effective teleoperation system can facilitate seamless collaboration and communication between humans and robots, enhancing their cooperative capabilities. This paper presents a motion-capture-based upper-body teleoperation system for humanoid robots, called TeleMotion, which consists of two key modules. The first module is an inertial sensor-based motion capture subsystem that accurately tracks human motion while remaining unaffected by environmental factors such as lighting and occlusion. The second module is a learnable temporal neural network inverse kinematics algorithm (TNIK) that fully leverages the relationship between historical human motion data and robotic joint angles. This allows for the rapid and precise mapping of human motion to humanoid motion. By integrating these two modules, TeleMotion enables a highly natural and intuitive interaction method for real-time teleoperation of humanoid robot.
https://eprints.bournemouth.ac.uk/41149/
Source: Scopus
TeleMotion: A Realtime Humanoid Teleoperation System with Motion Capture
Authors: Gan, J., Guo, S., Li, Z., Shi, X.
Journal: EXTENDED REALITY, ICXR 2024
Publication Date: 2025
Volume: 15461
Pages: 31-45
eISSN: 1611-3349
ISBN: 978-981-96-3678-5
ISSN: 0302-9743
DOI: 10.1007/978-981-96-3679-2_3
https://eprints.bournemouth.ac.uk/41149/
Source: Web of Science
TeleMotion: A Realtime Humanoid Teleoperation System with Motion Capture
Authors: Jiabao, G., Shihui, G., Zhijun, L., Shi, X.
Editors: Weitao, S., Frank, G., Shuai, L., Guofeng, Z.
Conference: ICXR 2024
Dates: 14/11/2024
Journal: Lecture Notes in Computer Science
Publication Date: 30/03/2025
Volume: 15461
Pages: 31-45
Publisher: Springer Nature
Place of Publication: Singapore
eISSN: 1611-3349
ISBN: 9789819636792
ISSN: 0302-9743
DOI: 10.1007/978-981-96-3679-2
Abstract:Teleoperation serves as a vital means of interaction between humans and robots, aiming to enable robots to move in accordance with human intentions. An effective teleoperation system can facilitate seamless collaboration and communication between humans and robots, enhancing their cooperative capabilities. This paper presents a motion-capture-based upper-body teleoperation system for humanoid robots, called TeleMotion, which consists of two key modules. The first module is an inertial sensor-based motion capture subsystem that accurately tracks human motion while remaining unaffected by environmental factors such as lighting and occlusion. The second module is a learnable temporal neural network inverse kinematics algorithm (TNIK) that fully leverages the relationship between historical human motion data and robotic joint angles. This allows for the rapid and precise mapping of human motion to humanoid motion. By integrating these two modules, TeleMotion enables a highly natural and intuitive interaction method for real-time teleoperation of humanoid robot.
https://eprints.bournemouth.ac.uk/41149/
Source: Manual