Papers
28
Total Citations
660
H-Index
13
About
Arren Glover is a robotics and computer vision researcher whose work sits at the cutting edge of neuromorphic and event-driven sensing technologies. Best known for pioneering contributions to event-based camera algorithms, Glover has fundamentally advanced how robots perceive and react to dynamic visual environments. His landmark 2016 paper on event-based Harris corner detection (167 citations) demonstrated that the inherent advantages of event-driven cameras — microsecond temporal resolution and low latency — could be harnessed to dramatically accelerate classical computer vision tasks such as feature detection, tracking, and optical flow. Building on this foundation, Glover developed robust visual tracking frameworks, event-driven ball detection systems, and independent motion detection algorithms, collectively accumulating hundreds of citations and establishing him as a leading voice in the field. His research extends into neuromorphic computing, including spiking neural networks deployed on Intel's Loihi chip for humanoid robot head-pose estimation, and practical software infrastructure enabling event-camera integration in real robotic systems. Applied primarily to the iCub humanoid robot platform, his work bridges perception and reactive control, with recent research on trajectory prediction for time-critical robotic tasks underscoring his continued commitment to enabling faster, smarter, and more efficient robot vision.
Research Focus
Key Achievements
Top Papers
- 1
- 2Event-driven ball detection and gaze fixation in clutter81 citations · 2016
- 3Robust visual tracking with a freely-moving event camera79 citations · 2017
- 4Towards Event-Driven Object Detection with Off-the-Shelf Deep Learning72 citations · 2018
- 5Independent motion detection with event-driven cameras39 citations · 2017
- 6
- 7
- 8A Controlled-Delay Event Camera Framework for On-Line Robotics22 citations · 2018
- 9Lingodroids: Studies in spatial cognition and language17 citations · 2011
- 10