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| Type | Conference or Workshop Paper |
| Scope | Discipline-based scholarship |
| Published in Proceedings | Yes |
| Title | Event-based Agile Object Catching with a Quadrupedal Robot |
| Organization Unit | |
| Authors |
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| Presentation Type | paper |
| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| ISBN | 979-8-3503-2365-8 |
| ISSN | 1050-4729 |
| Page Range | 12177 - 12183 |
| Event Title | 2023 IEEE International Conference on Robotics and Automation, ICRA 2023 |
| Event Type | conference |
| Event Location | London, United Kingdom of Great Britain and Northern Ireland |
| Event Start Date | May 29 - 2023 |
| Event End Date | June 2 - 2023 |
| Series Name | IEEE International Conference on Robotics and Automation. Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers |
| Abstract Text | Quadrupedal robots are conquering various applications in indoor and outdoor environments due to their capability to navigate challenging uneven terrains. Exteroceptive information greatly enhances this capability since perceiving their surroundings allows them to adapt their controller and thus achieve higher levels of robustness. However, sensors such as LiDARs and RGB cameras do not provide sufficient information to quickly and precisely react in a highly dynamic environment since they suffer from a bandwidth-latency trade-off. They require significant bandwidth at high frame rates while featuring significant perceptual latency at lower frame rates, thereby limiting their versatility on resource constrained platforms. In this work, we tackle this problem by equipping our quadruped with an event camera, which does not suffer from this tradeoff due to its asynchronous and sparse operation. In leveraging the low latency of the events, we push the limits of quadruped agility and demonstrate high-speed ball catching for the first time. We show that our quadruped equipped with an event-camera can catch objects with speeds up to 15 m/s from 4 meters, with a success rate of 83%. Using a VGA event camera, our method runs at 100 Hz on an NVIDIA Jetson Orin. |
| Digital Object Identifier | 10.1109/ICRA48891.2023.10161392 |
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