2007 European Control Conference (ECC) 2007
DOI: 10.23919/ecc.2007.7068806
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Autonomous SoC for fuzzy robot path tracking

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Cited by 8 publications
(10 citation statements)
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“…The aim of the tracker is to navigate the robot on the path, accounting for disturbances in the moving phase, e.g., wheel slippage, uneven terrain, localization uncertainty, etc. The study of path tracking has produced a vast amount of research literature ranging from classical control approaches (Altafini, 1999;Kamga & Rachid, 1997;Kanayama & Fahroo, 1997), to nonlinear control methodologies (Altafini, 2002;Egerstedt, Hu, & Stotsky, 1998;Koh & Cho, 1994;Samson, 1995;Wit, Crane, & Armstrong, 2004) to intelligent control strategies (Abdessemed, Benmahammed, & Monacelli, 2004;Antonelli, Chiaverini, & Fusco, 2007;Baltes & Otte, 1999;Cao & Hall, 1998;Deliparaschos, Moustris, & Tzafestas, 2007;El Hajjaji & Bentalba, 2003;Lee, Lam, Leung, & Tam, 2003;Liu & Lewis, 1994;Maalouf, Saad, & Saliah, 2006;Moustris & Tzafestas, 2005;Rodríguez-Castañ o, Heredia, & Ollero, 2000;Sanchez, Ollero, & Heredia, 1997;Xinxin, Kezhong, Muhe, & Bo, 1998). Of course, boundaries often blend since various approaches are used simultaneously.…”
Section: Introductionmentioning
confidence: 97%
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“…The aim of the tracker is to navigate the robot on the path, accounting for disturbances in the moving phase, e.g., wheel slippage, uneven terrain, localization uncertainty, etc. The study of path tracking has produced a vast amount of research literature ranging from classical control approaches (Altafini, 1999;Kamga & Rachid, 1997;Kanayama & Fahroo, 1997), to nonlinear control methodologies (Altafini, 2002;Egerstedt, Hu, & Stotsky, 1998;Koh & Cho, 1994;Samson, 1995;Wit, Crane, & Armstrong, 2004) to intelligent control strategies (Abdessemed, Benmahammed, & Monacelli, 2004;Antonelli, Chiaverini, & Fusco, 2007;Baltes & Otte, 1999;Cao & Hall, 1998;Deliparaschos, Moustris, & Tzafestas, 2007;El Hajjaji & Bentalba, 2003;Lee, Lam, Leung, & Tam, 2003;Liu & Lewis, 1994;Maalouf, Saad, & Saliah, 2006;Moustris & Tzafestas, 2005;Rodríguez-Castañ o, Heredia, & Ollero, 2000;Sanchez, Ollero, & Heredia, 1997;Xinxin, Kezhong, Muhe, & Bo, 1998). Of course, boundaries often blend since various approaches are used simultaneously.…”
Section: Introductionmentioning
confidence: 97%
“…Fuzzy logic path trackers have been used by several researchers (Abdessemed et al, 2004;Antonelli et al, 2007;Baltes & Otte, 1999;Cao & Hall, 1998;Deliparaschos et al, 2007;El Hajjaji & Bentalba, 2003;Jiangzhou, Sekhavat, & Laugier, 1999;Lee et al, 2003;Liu & Lewis, 1994;Moustris & Tzafestas, 2005;Ollero, Garcia-Cerezo, Martinez, & Mandow, 1997;Raimondi & Ciancimino, 2008;Rodríguez-Castañ o et al, 2000;Sanchez et al, 1997) since fuzzy logic provides a more intuitive way of analyzing and formulating the control actions, which bypasses most of the mathematical load needed to tackle such a highly nonlinear control problem. Furthermore, the fuzzy controller, that can be less complex in its implementation, is inherently robust to noise and parameter uncertainties.…”
Section: Introductionmentioning
confidence: 98%
“…The original Fuzzy Logic tracker is described in (Moustris & Tzafestas, 2005), and further modified in (Deliparaschos et al, 2007) in order to be implemented on a FPGA. Specifically the tracker is a zero-order Takagi-Sugeno FLC with the two inputs partitioned in nine triangular membership functions each, while the output is partitioned in five singletons (Fig.…”
Section: Fuzzy Logic Controllermentioning
confidence: 99%
“…Of course, boundaries often blend since various approaches are used simultaneously. Fuzzy logic path trackers have been used by several researchers (Abdessemed et al, 2004;Antonelli et al, 2007;Baltes & Otte, 1999;Cao & Hall, 1998;Deliparaschos et al, 2007;El Hajjaji & Bentalba, 2003;Jiangzhou et al, 1999;Lee et al, 2003;Liu & Lewis, 1994;Moustris & Tzafestas, 2011;Ollero et al, 1997;Raimondi & Ciancimino, 2008;Rodriguez-Castano et al, 2000;Sanchez et al, 1997) since fuzzy logic provides a more intuitive way for analysing and formulating the control actions, which bypasses most of the mathematical load needed to tackle such a highly nonlinear control problem. Furthermore, the fuzzy controller, which can be less complex in its implementation, is inherently robust to noise and parameter uncertainties.…”
Section: Introductionmentioning
confidence: 99%
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