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第16卷 智能系统学报 ·160· data[Cl//Proceedings of 2015 IEEE International Confer- [23]WEISS C,FROHLICH H,ZELL A.Vibration-based ter- ence on Robotics and Automation (ICRA).Seattle,WA. rain classification using support vector machines[C//In USA.2015 Proceedings of the IEEE/RSJ International Conference [11]KOLVENBACH H,BARTSCHI C.WELLHAUSEN L on Intelligent Robots and Systems (IROS).Beijing, et al.Haptic inspection of planetary soils with legged ro- China.2006:4429-4434. bots[J].IEEE robotics and automation letters,2019, [24]WEISS C.FROHLICH H.ZELL A.Vibration-based ter- 4(2:1626-1632. rain classification using support vector machines[C]// [12]MANDUCHI R,CASTANO A,TALUKDER A,et al. Proceedings of 2006 IEEE/RSJ International Confer- Obstacle detection and terrain classification for ence on Intelligent Robots and Systems.Beijing,China, autonomous off-road navigation.Auton[J].Autonomous 2006:4429-4434 robots,2005,18(1:81-102 [25]VICENTE A,LIU Jindong,YANG Guangzhong.Sur- [13]SANTAMARIA-NAVARRO A,TENIENTE E H. face classification based on vibration on omni-wheel MORTA M,et al.Terrain classification in complex mobile base[Cl//Proceedings of 2015 IEEE/RSJ Interna- three-dimensional outdoor environments[J].Journal of tional Conference on Intelligent Robots and Systems field robotics,2015,32(1):42-60. (IROS).Hamburg,Germany,2015:916-921. [14]ZHAO Kai,DONG Mingming,GU Liang.A new ter- [26]BAI Chengchao,GUO Jifeng,GUO Linli,et al.Deep rain classification framework using proprioceptive multi-layer perception based terrain classification for sensors for mobile robots[].Mathematical problems in planetary exploration rovers[J].Sensors,2019,19(4): engineering,2017:3938502. 3102. [15]PARK J,MIN K,KIM H.et al.Road surface classifica- [27]LUO Shan,BIMBO J.DAHIYA R,et al.Robotic tactile tion using a deep ensemble network with sensor feature perception of object properties:a review[J].Mechatron- selection[J].Sensors.2018.18(12):4342. ics.2017.48:54-67. [16]ROSENFELD R D,RESTREPO MG,GERARD W H, [28]KOZLOWSKI P,WALAS K.Deep neural networks for et al.Unsupervised surface classification to enhance the Terrain recognition task[C]//Proceedings of 2018 Baltic control performance of a UGV[C]//Proceedings of 2018 URSI Symposium.Poznan,Poland,2018:283-286. IEEE Systems and Information Engineering Design [29]Lomio F,Skenderi E,Mohamadi D,et al.Surface type Symposium.Charlottesville,VA,USA,2018. classification for autonomous robot indoor navigation[J]. [17]IAGNEMMA K D.DUBOWSKY S.Terrain estimation arXiv2019,arXiv:1905.00252v1. for high-speed rough-terrain autonomous vehicle naviga- [30]MARTINEZ-HERNANDEZ U,DODD T J, tion[C]//Proceedings of SPIE 4715,Unmanned Ground Vehicle Technology IV.Orlando,FL,United PRESCOTTTJ.Feeling the shape:active exploration States,2002. behaviors for object recognition with a robotic hand[J]. [18]BROOKS C A,IAGNEMMA K.Vibration-based ter- IEEE transactions on systems,man,and cybernetics: rain classification for planetary exploration rovers[J] systems,2017,48(12):2339-2348. IEEE transactions on robotic,2005,21(6):1185-1191. [31]OUDEYER P Y,KAPLAN F,HAFNER VV.Intrinsic [19]BROOKS C A,IAGNEMMA K.Self-supervised terrain motivation systems for autonomous mental develop- classification for planetary surface exploration rovers[J]. ment[J].IEEE transactions on evolutionary computation, Journal of field robotics,2012.29(3):445-468. 2007,11(2:265-286 [20]OJEDA L,BORENSTEIN J,WITUS G,et al.Terrain [32]GOTTLIEB J,OUDEYER P Y,LOPES M,et al.In characterization and classification with a mobile formation-seeking,curiosity,and attention:computation- robot[J].Journal of field robot,2006,2:103-122. al and neural mechanisms[J].Information-seeking,curi- [21]WONG C,YANG Erfu,YAN Xiutian,et al.Adaptive osity,and attention:computational and neural mechan- and intelligent navigation of autonomous planetary isms.2013,17(11)585-593. rovers-a survey[C]//Proceedings of 2017 NASA/ESA 作者简介: Conference on Adaptive Hardware and Systems (AHS) 张威,硕士研究生,主要研究方向 Pasadena,CA.USA,2017:237-244. 为移动机器人控制、感知与学习。 [22]ZHANG Shuo,LIU Shaochuang,MA Youqing,et al. Self calibration of the stereo vision system of the Chang e-3 lunar rover based on the bundle block adjustment[J]. ISPRS journal of photogrammetry and remote sensing, 2017.128:287-297.data[C]//Proceedings of 2015 IEEE International Confer￾ence on Robotics and Automation (ICRA). Seattle, WA, USA, 2015. KOLVENBACH H, BÄRTSCHI C, WELLHAUSEN L, et al. Haptic inspection of planetary soils with legged ro￾bots[J]. IEEE robotics and automation letters, 2019, 4(2): 1626–1632. [11] MANDUCHI R, CASTANO A, TALUKDER A, et al. Obstacle detection and terrain classification for autonomous off-road navigation. Auton[J]. Autonomous robots, 2005, 18(1): 81–102. [12] SANTAMARIA-NAVARRO À, TENIENTE E H, MORTA M, et al. Terrain classification in complex three-dimensional outdoor environments[J]. Journal of field robotics, 2015, 32(1): 42–60. [13] ZHAO Kai, DONG Mingming, GU Liang. A new ter￾rain classification framework using proprioceptive sensors for mobile robots[J]. Mathematical problems in engineering, 2017: 3938502. [14] PARK J, MIN K, KIM H, et al. Road surface classifica￾tion using a deep ensemble network with sensor feature selection[J]. Sensors, 2018, 18(12):4342. [15] ROSENFELD R D, RESTREPO M G, GERARD W H, et al. Unsupervised surface classification to enhance the control performance of a UGV[C]//Proceedings of 2018 IEEE Systems and Information Engineering Design Symposium. Charlottesville, VA, USA, 2018. [16] IAGNEMMA K D, DUBOWSKY S. Terrain estimation for high-speed rough-terrain autonomous vehicle naviga￾tion[C]//Proceedings of SPIE 4715, Unmanned Ground Vehicle Technology IV. Orlando, FL, United States, 2002. [17] BROOKS C A, IAGNEMMA K. Vibration-based ter￾rain classification for planetary exploration rovers[J]. IEEE transactions on robotic, 2005, 21(6): 1185–1191. [18] BROOKS C A, IAGNEMMA K. Self-supervised terrain classification for planetary surface exploration rovers[J]. Journal of field robotics, 2012, 29(3): 445–468. [19] OJEDA L, BORENSTEIN J, WITUS G, et al. Terrain characterization and classification with a mobile robot[J]. Journal of field robot, 2006, 2: 103–122. [20] WONG C, YANG Erfu, YAN Xiutian, et al. Adaptive and intelligent navigation of autonomous planetary rovers—a survey[C]//Proceedings of 2017 NASA/ESA Conference on Adaptive Hardware and Systems (AHS). Pasadena, CA, USA, 2017: 237–244. [21] ZHANG Shuo, LIU Shaochuang, MA Youqing, et al. Self calibration of the stereo vision system of the Chang’ e-3 lunar rover based on the bundle block adjustment[J]. ISPRS journal of photogrammetry and remote sensing, 2017, 128: 287–297. [22] WEISS C, FROHLICH H, ZELL A. Vibration-based ter￾rain classification using support vector machines[C]// In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Beijing, China, 2006:4429–4434. [23] WEISS C, FROHLICH H, ZELL A. Vibration-based ter￾rain classification using support vector machines[C]// Proceedings of 2006 IEEE/RSJ International Confer￾ence on Intelligent Robots and Systems. Beijing, China, 2006: 4429–4434 [24] VICENTE A, LIU Jindong, YANG Guangzhong. Sur￾face classification based on vibration on omni-wheel mobile base[C]//Proceedings of 2015 IEEE/RSJ Interna￾tional Conference on Intelligent Robots and Systems (IROS). Hamburg, Germany, 2015: 916–921. [25] BAI Chengchao, GUO Jifeng, GUO Linli, et al. Deep multi-layer perception based terrain classification for planetary exploration rovers[J]. Sensors, 2019,19(4): 3102. [26] LUO Shan, BIMBO J, DAHIYA R, et al. Robotic tactile perception of object properties: a review[J]. Mechatron￾ics, 2017, 48: 54–67. [27] KOZLOWSKI P, WALAS K. Deep neural networks for Terrain recognition task[C]//Proceedings of 2018 Baltic URSI Symposium. Poznan, Poland, 2018: 283–286. [28] Lomio F, Skenderi E, Mohamadi D, et al. Surface type classification for autonomous robot indoor navigation[J]. arXiv 2019, arXiv: 1905.00252v1. [29] MARTINEZ-HERNANDEZ U, DODD T J, PRESCOTT T J. Feeling the shape: active exploration behaviors for object recognition with a robotic hand[J]. IEEE transactions on systems, man, and cybernetics: systems, 2017, 48(12): 2339–2348. [30] OUDEYER P Y, KAPLAN F, HAFNER V V. Intrinsic motivation systems for autonomous mental develop￾ment[J]. IEEE transactions on evolutionary computation, 2007, 11(2): 265–286. [31] GOTTLIEB J, OUDEYER P Y, LOPES M, et al. In￾formation-seeking, curiosity, and attention: computation￾al and neural mechanisms[J]. Information-seeking, curi￾osity, and attention: computational and neural mechan￾isms, 2013, 17(11): 585–593. [32] 作者简介: 张威,硕士研究生,主要研究方向 为移动机器人控制、感知与学习。 第 16 卷 智 能 系 统 学 报 ·160·
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