{"ID":2886765,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.02153","arxiv_id":"2508.02153","title":"Towards High Precision: An Adaptive Self-Supervised Learning Framework for Force-Based Verification","abstract":"The automation of robotic tasks requires high precision and adaptability, particularly in force-based operations such as insertions. Traditional learning-based approaches either rely on static datasets, which limit their ability to generalize, or require frequent manual intervention to maintain good performances. As a result, ensuring long-term reliability without human supervision remains a significant challenge. To address this, we propose an adaptive self-supervised learning framework for insertion classification that continuously improves its precision over time. The framework operates in real-time, incrementally refining its classification decisions by integrating newly acquired force data. Unlike conventional methods, it does not rely on pre-collected datasets but instead evolves dynamically with each task execution. Through real-world experiments, we demonstrate how the system progressively reduces execution time while maintaining near-perfect precision as more samples are processed. This adaptability ensures long-term reliability in force-based robotic tasks while minimizing the need for manual intervention.","short_abstract":"The automation of robotic tasks requires high precision and adaptability, particularly in force-based operations such as insertions. Traditional learning-based approaches either rely on static datasets, which limit their ability to generalize, or require frequent manual intervention to maintain good performances. As a...","url_abs":"https://arxiv.org/abs/2508.02153","url_pdf":"https://arxiv.org/pdf/2508.02153v2","authors":"[\"Zebin Duan\",\"Frederik Hagelskjær\",\"Aljaz Kramberger\",\"Juan Heredia\",\"Norbert Krüger\"]","published":"2025-08-04T07:49:59Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[]","has_code":false}