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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2406.00869 |
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Table of Contents:
- This paper explores the use of 3D lidar in a physical Human-Robot Interaction (pHRI) scenario. To achieve the aforementioned, experiments were conducted to mimic a modern shop-floor environment. Data was collected from a pool of seventeen participants while performing pre-determined tasks in a shared workspace with the robot. To demonstrate an end-to-end case; a perception pipeline was developed that leverages reflectivity, signal, near-infrared, and point-cloud data from a 3-D lidar. This data is then used to perform safety based control whilst satisfying the speed and separation monitoring (SSM) criteria. In order to support the perception pipeline, a state-of-the-art object detection network was leveraged and fine-tuned by transfer learning. An analysis is provided along with results of the perception and the safety based controller. Additionally, this system is compared with the previous work.