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--- abstract: | Decades of research into the structure and function of the cerebellum have led to a clear understanding of many of its cells, as well as how learning takes place. Furthermore, there are many theories on what signals the cerebellum operates on, and how it works in concert with other parts of the nervous system. Nevertheless, the application of computational cerebellar models to the control of robot dynamics remains in its infant state. To date, a few applications have been realized, yet limited to the control of traditional robot structures which, strictly speaking, do not require adaptive control for the tasks that are performed since their dynamic structures are relatively simple. The currently emerging family of light-weight robots poses a new challenge to robot control: due to their complex dynamics traditional methods, depending on a full analysis of the dynamics of the system, are no longer applicable since the joints influence each other dynamics during movement. Can artificial cerebellar models compete here? In this overview paper we present a succinct introduction of the cerebellum, and discuss where it could be applied to tackle problems in robotics. Without conclusively answering the above question, an overview of several applications of cerebellar models to robot control is given. altloc: - http://www.robotic.dlr.de/Smagt/papers/Sma98a.pdf chapter: ~ commentary: ~ commref: ~ confdates: ~ conference: ~ confloc: ~ contact_email: ~ creators_id: [] creators_name: - family: van der Smagt given: Patrick honourific: '' lineage: '' date: 1998 date_type: published datestamp: 2001-02-26 department: ~ dir: disk0/00/00/13/22 edit_lock_since: ~ edit_lock_until: ~ edit_lock_user: ~ editors_id: [] editors_name: [] eprint_status: archive eprintid: 1322 fileinfo: /style/images/fileicons/application_postscript.png;/1322/1/Sma98a.ps.gz|/style/images/fileicons/application_pdf.png;/1322/4/Sma98a.pdf full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: pub issn: ~ item_issues_comment: [] item_issues_count: 0 item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: |2 cerebellum, robot dynamics, robot arm control, computational cerebellar models, neural networks lastmod: 2011-03-11 08:54:35 latitude: ~ longitude: ~ metadata_visibility: show note: ~ number: ~ pagerange: 301-320 pubdom: FALSE publication: Connection Science publisher: ~ refereed: TRUE referencetext: | \bibitem[\protect\BCAY{Aguilar \BBA{} Contreras-Vidal}{Aguilar \BBA{} Contreras-Vidal}{1994}]{AguCon:94} Aguilar, J.~M.\BCBT{} \BBA{} Contreras-Vidal, J.~L. \newblock{}\BBOP{}1994\BBCP{}. \newblock{}\BBOQ{}{NAVITE}: A neural network system for sensory-based robot navigation.\BBCQ{} \newblock{}In \Bem{Proceedings of the World Congress on Neural Networks}\ (\BVOL~II, \BPGS\ 177--182). \newblock{}Lawrence Erlbaum, Hillsdale, New Jersey. \bibitem[\protect\BCAY{Aiba \BOthers{}}{Aiba \BOthers{}}{1994}]{Aib94} Aiba, A., Kano, M., Chen, C., Stanton, M., Fox, G., Herrup, K., Zwingman, T.\BCBL{} \BBA{} Tonegawa, S. \newblock{}\BBOP{}1994\BBCP{}. \newblock{}\BBOQ{}Deficient cerebellar long-term depression and impaired motor learning in {mGluR1} mutant mice.\BBCQ{} \newblock{}\Bem{Cell}, \Bem{79}, 377--388. \bibitem[\protect\BCAY{Albus}{Albus}{1971}]{Alb71} Albus, J. \newblock{}\BBOP{}1971\BBCP{}. \newblock{}\BBOQ{}A theory of cerebellar function.\BBCQ{} \newblock{}\Bem{Mathematical Bioscience}, \Bem{10}, 25--61. \bibitem[\protect\BCAY{Albus}{Albus}{1975}]{Alb75} Albus, J. \newblock{}\BBOP{}1975\BBCP{}. \newblock{}\BBOQ{}A new approach to manipulator control: The cerebellar model articulation controller ({CMAC}).\BBCQ{} \newblock{}\Bem{Journal of Dynamic Systems, Measurement and Control, Transactions of the {ASME}, series G}, \Bem{97}, 270--277. \bibitem[\protect\BCAY{Artola \BBA{} Singer}{Artola \BBA{} Singer}{1993}]{ArtSin93} Artola, A.\BCBT{} \BBA{} Singer, W. \newblock{}\BBOP{}1993\BBCP{}. \newblock{}\BBOQ{}Long-term depression of excitatory synaptic transmission and its relationship to long-term potentiation.\BBCQ{} \newblock{}\Bem{Trends in Neuroscience}, \Bem{16}, 480--487. \bibitem[\protect\BCAY{Atkeson \BBA{} Hollerbach}{Atkeson \BBA{} Hollerbach}{1985}]{AtkHol85} Atkeson, C.\BCBT{} \BBA{} Hollerbach, J. \newblock{}\BBOP{}1985\BBCP{}. \newblock{}\BBOQ{}Kinematic features of unrestrained vertical arm movements.\BBCQ{} \newblock{}\Bem{Journal of Neuroscience}, \Bem{5}, 2318--2330. \bibitem[\protect\BCAY{Barto, Buckingham\BCBL{} \BBA{} Houk}{Barto \BOthers{}}{1995}]{BarBucHou95} Barto, A.~G., Buckingham, J.~T.\BCBL{} \BBA{} Houk, J.~C. \newblock{}\BBOP{}1995\BBCP{}. \newblock{}\BBOQ{}A predictive switching model of cerebellar movement control.\BBCQ{} \newblock{}In D.~S. 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