{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deep-neural-network-based-subspace-learning","title":"Deep Neural Network Based Subspace Learning of Robotic Manipulator Workspace Mapping","arxiv_id":"1804.08951","date":"2018-04-24","proceeding":null,"authors":["Peiyuan Liao"],"abstract":"The manipulator workspace mapping is an important problem in robotics and has\nattracted significant attention in the community. However, most of the\npre-existing algorithms have expensive time complexity due to the reliance on\nsophisticated kinematic equations. To solve this problem, this paper introduces\nsubspace learning (SL), a variant of subspace embedding, where a set of robot\nand scope parameters is mapped to the corresponding workspace by a deep neural\nnetwork (DNN). Trained on a large dataset of around $\\mathbf{6\\times 10^4}$\nsamples obtained from a MATLAB$^\\circledR$ implementation of a classical method\nand sampling of designed uniform distributions, the experiments demonstrate\nthat the embedding significantly reduces run-time from $\\mathbf{5.23 \\times\n10^3}$ s of traditional discretization method to $\\mathbf{0.224}$ s, with high\naccuracies (average F-measure is $\\mathbf{0.9665}$ with batch gradient descent\nand resilient backpropagation).","url_abs":"http://arxiv.org/abs/1804.08951v2","url_pdf":"http://arxiv.org/pdf/1804.08951v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"deep-neural-network-based-subspace-learning","repo_url":"https://github.com/liaopeiyuan/Subspace-Learning","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}