Divide et Impera: Decoding Impedance Strategies for Robotic Peg-in-Hole Assembly
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866917949339598848 |
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| author | Lachner, Johannes Tessari, Federico West Jr., A. Michael Nah, Moses C. Hogan, Neville |
| author_facet | Lachner, Johannes Tessari, Federico West Jr., A. Michael Nah, Moses C. Hogan, Neville |
| contents | This paper investigates robotic peg-in-hole assembly using the Elementary Dynamic Actions (EDA) framework, which models contact-rich tasks through a combination of submovements, oscillations, and mechanical impedance. Rather than focusing on a single optimal parameter set, we analyze the distribution and structure of multiple successful impedance solutions, revealing patterns that guide impedance selection in contactrich robotic manipulation. Experiments with a real robot and four different peg types demonstrate the presence of task-specific and generalized assembly strategies, identified through K-means Clustering. Principal Component Analysis (PCA) is used to represent these findings, highlighting patterns in successful impedance selections. Additionally, a neural-network-based success predictor accurately estimates feasible impedance parameters, reducing the need for extensive trial-and-error tuning. By providing publicly available code, CAD files, and a trained model, this work enhances the accessibility of impedance control and offers a structured approach to programming robotic assembly tasks, particularly for less-experienced users. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_01054 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Divide et Impera: Decoding Impedance Strategies for Robotic Peg-in-Hole Assembly Lachner, Johannes Tessari, Federico West Jr., A. Michael Nah, Moses C. Hogan, Neville Robotics This paper investigates robotic peg-in-hole assembly using the Elementary Dynamic Actions (EDA) framework, which models contact-rich tasks through a combination of submovements, oscillations, and mechanical impedance. Rather than focusing on a single optimal parameter set, we analyze the distribution and structure of multiple successful impedance solutions, revealing patterns that guide impedance selection in contactrich robotic manipulation. Experiments with a real robot and four different peg types demonstrate the presence of task-specific and generalized assembly strategies, identified through K-means Clustering. Principal Component Analysis (PCA) is used to represent these findings, highlighting patterns in successful impedance selections. Additionally, a neural-network-based success predictor accurately estimates feasible impedance parameters, reducing the need for extensive trial-and-error tuning. By providing publicly available code, CAD files, and a trained model, this work enhances the accessibility of impedance control and offers a structured approach to programming robotic assembly tasks, particularly for less-experienced users. |
| title | Divide et Impera: Decoding Impedance Strategies for Robotic Peg-in-Hole Assembly |
| topic | Robotics |
| url | https://arxiv.org/abs/2410.01054 |