{"ID":23507315,"CreatedAt":"2026-09-18T02:21:44.056544415Z","UpdatedAt":"2026-09-20T18:11:56.143995915Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2609.20499","arxiv_id":"2609.20499","title":"Towards AI-enhanced control: a numerical technique for trajectory smoothing of a parallel robot for pancreatic surgery","abstract":"The paper presents a numerical approach for the end-effector trajectory smoothing of a parallel robot designed for minimally invasive pancreatic surgery. The approach is tailored for real-time master-slave control architecture and uses a 3D space mouse for command input for velocity control. The trajectory smoothing is achieved by generating S-curves in the end-effector velocity fields, thus controlling the accelerations, which in turn reduces tissue trauma in the minimally invasive procedures. Real-time control is enabled by segmenting the S-curves based on the command inputs from the 3D space mouse. A special case is considered where the acceleration time is constant for all command inputs. Numeric results demonstrate stable transitions (without abrupt changes) in both the end-effector parameter space and in the active joints parameters, thereby validating the proposed approach. Further work aims to test the approach on an experimental model and integrate it into AI-based training modules.","short_abstract":"The paper presents a numerical approach for the end-effector trajectory smoothing of a parallel robot designed for minimally invasive pancreatic surgery. The approach is tailored for real-time master-slave control architecture and uses a 3D space mouse for command input for velocity control. The trajectory smoothing is...","url_abs":"https://arxiv.org/abs/2609.20499","url_pdf":"https://arxiv.org/pdf/2609.20499v1","authors":"[\"Iosif Birlescu\",\"Alexandru Pusca\",\"Bogdan Gherman\",\"Calin Vaida\",\"Ionut Zima\",\"Damien Chablat\",\"Doina Pisla\"]","published":"2026-09-17T14:47:20Z","proceeding":"cs.RO","tasks":"[\"cs.RO\"]","methods":"[]","has_code":false}