Latent Representations for Visual Proprioception in Inexpensive Robots

• URL: http://arxiv.org/abs/2504.14634v2
• Date: Thu, 24 Apr 2025 12:36:35 GMT
• Title: Latent Representations for Visual Proprioception in Inexpensive Robots
• Authors: Sahara Sheikholeslami, Ladislau Bölöni,
• Abstract summary: We ask: to what extent can a fast, single-pass regression architecture perform visual proprioception from a single external camera image?<n>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.<n>We evaluate the achievable accuracy through experiments on an inexpensive 6-DoF robot.
• Score: 7.0579376123869935
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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