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Slip estimation methods for proprioceptive terrain classification using tracked mobile robots

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dc.contributor.author Masha, Ditebogo F
dc.contributor.author Burke, Michael G
dc.contributor.author Twala, B
dc.date.accessioned 2018-02-07T10:34:44Z
dc.date.available 2018-02-07T10:34:44Z
dc.date.issued 2017-11
dc.identifier.citation Masha, D.F., Burke, M.G. and Twala, B. 2017. Slip estimation methods for proprioceptive terrain classification using tracked mobile robots. 2017 Pattern Recognition Association of South Africa and Robotics and Mechatronics International Conference (PRASA-RobMech), 30 November - 1 December 2017, Bloemfontein, South Africa en_US
dc.identifier.isbn 978-1-5386-2314-5
dc.identifier.isbn 978-1-5386-2313-8
dc.identifier.isbn 978-1-5386-2315-2
dc.identifier.uri http://ieeexplore.ieee.org/document/8261139/
dc.identifier.uri DOI: 10.1109/RoboMech.2017.8261139
dc.identifier.uri http://hdl.handle.net/10204/10027
dc.description Copyright: 2017 IEEE. Due to copyright restrictions, the attached PDF file contains the accepted version of the published item. For access to the published version, please consult the publisher's website. en_US
dc.description.abstract Recent work has shown that proprioceptive measurements such as terrain slip can be used for terrain classification. This paper investigates the suitability of four simple slip estimation methods for differentiating between indoor and outdoor terrain surfaces, namely: rocks, grass, rubber and carpet. These slip estimates are calculated using experimental odometric data collected from a tracked autonomous ground vehicle and comprise of two instantaneous estimators and a temporal windowing approach. Results show that only the temporal windowing approach shows significant differences across the terrains investigated, indicating that instantaneous measurements are unsuited to terrain classification. en_US
dc.language.iso en en_US
dc.publisher IEEE en_US
dc.relation.ispartofseries Worklist;20145
dc.subject Slip estimation en_US
dc.subject Terrain classification en_US
dc.subject Surface differentiation en_US
dc.subject Tracked vehicles en_US
dc.subject Proprioceptive terrain classification en_US
dc.title Slip estimation methods for proprioceptive terrain classification using tracked mobile robots en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Masha, D. F., Burke, M. G., & Twala, B. (2017). Slip estimation methods for proprioceptive terrain classification using tracked mobile robots. IEEE. http://hdl.handle.net/10204/10027 en_ZA
dc.identifier.chicagocitation Masha, Ditebogo F, Michael G Burke, and B Twala. "Slip estimation methods for proprioceptive terrain classification using tracked mobile robots." (2017): http://hdl.handle.net/10204/10027 en_ZA
dc.identifier.vancouvercitation Masha DF, Burke MG, Twala B, Slip estimation methods for proprioceptive terrain classification using tracked mobile robots; IEEE; 2017. http://hdl.handle.net/10204/10027 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Masha, Ditebogo F AU - Burke, Michael G AU - Twala, B AB - Recent work has shown that proprioceptive measurements such as terrain slip can be used for terrain classification. This paper investigates the suitability of four simple slip estimation methods for differentiating between indoor and outdoor terrain surfaces, namely: rocks, grass, rubber and carpet. These slip estimates are calculated using experimental odometric data collected from a tracked autonomous ground vehicle and comprise of two instantaneous estimators and a temporal windowing approach. Results show that only the temporal windowing approach shows significant differences across the terrains investigated, indicating that instantaneous measurements are unsuited to terrain classification. DA - 2017-11 DB - ResearchSpace DP - CSIR KW - Slip estimation KW - Terrain classification KW - Surface differentiation KW - Tracked vehicles KW - Proprioceptive terrain classification LK - https://researchspace.csir.co.za PY - 2017 SM - 978-1-5386-2314-5 SM - 978-1-5386-2313-8 SM - 978-1-5386-2315-2 T1 - Slip estimation methods for proprioceptive terrain classification using tracked mobile robots TI - Slip estimation methods for proprioceptive terrain classification using tracked mobile robots UR - http://hdl.handle.net/10204/10027 ER - en_ZA


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