Achieving Human-Like Movements with Neural Network-Based Planner in Collaborative Robotics
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2025
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| _version_ | 1866901653144207360 |
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| author | Lozer, Federico Scalera, Lorenzo Gasparetto, Alessandro Brandstotter, Mathias |
| author_facet | Lozer, Federico Scalera, Lorenzo Gasparetto, Alessandro Brandstotter, Mathias |
| contents | This work presents a neural network-based motion planning approach designed to allow redundant robotic manipulators to emulate the arm movements of a human subject, by selecting the optimal kinematic configuration. The proposed approach is developed with the aim of improving human-robot collaboration in terms of acceptability and trustability. Experimental results on a robot with 7 degrees of freedom demonstrate the feasibility and the effectiveness of the proposed approach, in correctly replicating the motion of a human arm. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17629638 |
| institution | Zenodo |
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| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Achieving Human-Like Movements with Neural Network-Based Planner in Collaborative Robotics Lozer, Federico Scalera, Lorenzo Gasparetto, Alessandro Brandstotter, Mathias trajectory planning neural network artificial intelligence collaborative robotics redundancy This work presents a neural network-based motion planning approach designed to allow redundant robotic manipulators to emulate the arm movements of a human subject, by selecting the optimal kinematic configuration. The proposed approach is developed with the aim of improving human-robot collaboration in terms of acceptability and trustability. Experimental results on a robot with 7 degrees of freedom demonstrate the feasibility and the effectiveness of the proposed approach, in correctly replicating the motion of a human arm. |
| title | Achieving Human-Like Movements with Neural Network-Based Planner in Collaborative Robotics |
| topic | trajectory planning neural network artificial intelligence collaborative robotics redundancy |
| url | https://doi.org/10.5281/zenodo.17629638 |