| Issue |
EPJ Web Conf.
Volume 367, 2026
Fifth International Conference on Robotics, Intelligent Automation and Control Technologies (RIACT 2026)
|
|
|---|---|---|
| Article Number | 01009 | |
| Number of page(s) | 15 | |
| Section | Robotics Design and Control | |
| DOI | https://doi.org/10.1051/epjconf/202636701009 | |
| Published online | 29 April 2026 | |
https://doi.org/10.1051/epjconf/202636701009
Real-Time Object Tracking Using Event-Based Imaging in Cable-Driven Robotic Systems
1 Institute of Robotics and Mechatronics, University of Applied Sciences Bochum, Bochum, Germany
2 Faculty of Mechatronics and Mechanical Engineering Bochum, University of Applied Sciences Bochum, Bochum, Germany
3 Department of Control Engineering and Machine Vision, University of Applied Sciences Bochum, Bochum, Germany
4 Department of Engineering Mechanics, University of Applied Sciences Bochum, Bochum, Germany
5 School of Mechanical Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India
Published online: 29 April 2026
Abstract
Event-based image processing represents an emerging research field within computer vision and is gaining increasing relevance in modern imaging technologies. In contrast to conventional frame-based approaches, neuromorphic image sensors record only positive and negative changes in light intensity at the pixel level. This enables data acquisition with temporal resolution in the microsecond range, thereby opening up novel approaches for the real-time capture and analysis of highly dynamic scenes. This Paper investigates event-based imaging (EBI) as a novel sensing technology for high-precision object tracking in a high-speed cable-driven robot. First, a fundamental overview of the operating principles and characteristic properties of event-based image sensors is provided, and their potential for capturing highly dynamic scenes is discussed. Subsequently, a systematic comparison with conventional frame-based image processing methods is conducted, particularly with respect to temporal resolution, latency, and robustness under real operating conditions. Building on these considerations, the development and implementation of an event-based sensor system for real-time position estimation in the cable-driven robot are presented. The performance of the system is analyzed and evaluated through experimental investigations, with a focus on rapid object detection and the precise capture of dynamic motion patterns.
Key words: Event-Based Imaging / Neuromorphic Vision / Real-Time Object Tracking / Motion Detection / Event Stream Processing / Dynamic Vision Sensor / High-Speed Imaging / Machine Vision
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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