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These methods can be used in a standalone fashion, but we also show how embedding these into a hybrid neuro-genetic IK pipeline allows for further optimization via sequential least-squares programming (SLSQP) or a genetic algorithm (GA). The models are trained and tested on dense datasets that were collected from random robot configurations of the new Neuro-Inspired COLlaborator (NICOL), a semi-humanoid robot with two redundant 8-DoF manipulators. We utilize the weighted multi-objective function from the state-of-the-art BioIK method to support the training process and our hybrid neuro-genetic architecture. We show that the neural models can compete with state-of-the-art IK approaches, which allows for deployment directly to robotic hardware. Additionally, it is shown that the incorporation of the genetic algorithm improves the precision while simultaneously reducing the overall runtime.<\/jats:p>","DOI":"10.1007\/978-3-031-44207-0_38","type":"book-chapter","created":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T14:03:51Z","timestamp":1695305031000},"page":"457-470","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["CycleIK: Neuro-inspired Inverse Kinematics"],"prefix":"10.1007","author":[{"given":"Jan-Gerrit","family":"Habekost","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erik","family":"Strahl","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philipp","family":"Allgeuer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Matthias","family":"Kerzel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Wermter","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,9,22]]},"reference":[{"key":"38_CR1","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1007\/978-3-642-25324-9_42","volume-title":"Advances in Artificial Intelligence","author":"OA Aguilar","year":"2011","unstructured":"Aguilar, O.A., Huegel, J.C.: Inverse\u00a0kinematics\u00a0solution\u00a0for\u00a0robotic manipulators\u00a0using\u00a0a\u00a0CUDA-based parallel\u00a0genetic\u00a0algorithm. 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