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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.14634 |
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| _version_ | 1866915873059504128 |
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| author | Sheikholeslami, Sahara Bölöni, Ladislau |
| author_facet | Sheikholeslami, Sahara Bölöni, Ladislau |
| contents | Robotic manipulation requires explicit or implicit knowledge of the robot's joint positions. Precise proprioception is standard in high-quality industrial robots but is often unavailable in inexpensive robots operating in unstructured environments. In this paper, we ask: to what extent can a fast, single-pass regression architecture perform visual proprioception from a single external camera image, available even in the simplest manipulation settings? We explore several latent representations, including CNNs, VAEs, ViTs, and bags of uncalibrated fiducial markers, using fine-tuning techniques adapted to the limited data available. We evaluate the achievable accuracy through experiments on an inexpensive 6-DoF robot. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_14634 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Latent Representations for Visual Proprioception in Inexpensive Robots Sheikholeslami, Sahara Bölöni, Ladislau Robotics Computer Vision and Pattern Recognition Robotic manipulation requires explicit or implicit knowledge of the robot's joint positions. Precise proprioception is standard in high-quality industrial robots but is often unavailable in inexpensive robots operating in unstructured environments. In this paper, we ask: to what extent can a fast, single-pass regression architecture perform visual proprioception from a single external camera image, available even in the simplest manipulation settings? We explore several latent representations, including CNNs, VAEs, ViTs, and bags of uncalibrated fiducial markers, using fine-tuning techniques adapted to the limited data available. We evaluate the achievable accuracy through experiments on an inexpensive 6-DoF robot. |
| title | Latent Representations for Visual Proprioception in Inexpensive Robots |
| topic | Robotics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2504.14634 |