用户名: 密码: 验证码:
基于嗅觉信息的机器人味源定位策略及实验研究
详细信息    本馆镜像全文|  推荐本文 |  |   获取CNKI官网全文
摘要
随着各国对国家安全、社会治安等公共事业的高度重视,研究能在有毒、易燃易爆等危险环境中代替人类工作的危险作业机器人系统具有重要的理论和实际意义。目前,如何实现移动机器人对可疑目标的准确判断,迅速确定毒气泄漏源或可疑目标的具体位置,是应用移动机器人执行危险作业亟待解决的关键问题。
     本论文在国家863计划项目“极限环境下面向危险品检测的多感官机器人系统”(项目编号:2006AA04Z221)的支持下,利用所研制的多感官拟人机器人头部系统,与移动机器人本体相结合,针对搜寻有毒气体泄漏源的应用,对机器人味源定位策略进行了深入研究。为应用移动机器人完成各种与气味相关的危险工作奠定了基础。
     本文的创新性工作包括:
     1、研制了一套具有视觉、嗅觉及听觉功能的多感官拟人机器人头部系统。在分析人的头部运动形式的基础上,综合考虑机器人头部的几何尺寸、运动学及动力学等因素,设计了4自由度拟人机器人头部结构。该结构采用一种变形的万向节式结构,通过串联式关节的形式实现了头部的三种运动,两级自由度完成的屈伸运动范围可达±30o,旋转运动范围为±90o,侧屈运动范围为±20o。基于CAN总线设计了分布式控制系统,该系统具有结构简单、实时性好、可靠性高的优点。
     2、基于仿生学原理,提出并设计了一种新的机器人仿生嗅觉系统,具有类似人的鼻腔结构及相当于人肺功能的吸气系统,能够同时检测CO、SO2、H2S、O2及一种可挥发性有机化合物气体。采用电化学和光离子气体传感器,恢复时间快,选择性强,可大大提高机器人嗅觉能力,并且根据目标气体可方便的更换相应气体传感器。系统采用C8051F020单片机实现,通过串口与机器人主控机通讯。该系统结构紧凑,性能不受安装位置影响,可作为机器人标准化组件组装到各种类型的机器人上,以帮助其完成与嗅觉有关的工作。
     3、受动物捕食策略的启发,提出了一种基于动物捕食行为的机器人味源定位策略,融合了气体传感器、风向传感器、超声传感器等传感器信息,整合了“Z”形搜索、逆风搜索,模糊神经网络搜索等多种较优的搜索算法。采用了基于行为的包容式控制结构,设计了针对各种搜索算法的行为模块,使机器人在搜寻味源过程中自适应地选择较优的搜索策略。实验结果表明,该策略具有较强的鲁棒性,能够适应室内自然环境下的味源定位需要。
     4、借鉴人类综合利用除嗅觉以外的其它感官功能进行味源定位的方法,提出了一种融合嗅觉、视觉信息的机器人味源定位策略,建立了基于气味信息、颜色信息和距离信息融合的味源模型库,帮助机器人进行味源的搜寻和确认。针对该策略,设计了基于多层黑板模型的机器人嗅觉定位控制系统,通过搜寻味源黑板和确认味源黑板协调工作实现机器人味源定位。通过实验验证了该策略具有最高的效率和成功率,具有较强的环境适应能力。
As greater and greater importance is attached to the public utilities such as national security and public order, the research on the system of the robot that can replace human beings in the toxic, explosive and other dangerous environments to perform a mission so as to free them from working in danger is of great theoretical and practical significance. At present , in order to make robot do the dangerous work for human beings, the key problem to be urgently solved is how to realize the mobile robot’s accurate judgments of the suspicious targets and its quick determination of the source of toxic gas or the location of the suspicious targets.
     This paper is supported by the Hi-tech Research and Development Program of China -- the Multi-Sensory Robot System of Detecting Dangerous Goods in Extreme Environments (No. 2006AA04Z221). It combines the mobile robot with the multi-sensory humaniod robot head system, and according to the application of seeking the toxic gas source, it makes a deep research into the strategy of robot odor source localization, which lays a foundation for the application of mobile robot to carry out various odor-related dangerous tasks.
     This paper covers the following original points:
     1. This paper develops a humaniod robot head system with multi-sensory functions of vision, olfaction and hearing. Based on the analysis of human heads and a comprehensive consideration of such factors as the geometric size of the robot head, the kinematics and dynamics, this paper devises a 4-DOF structure of the humaniod robot head. This structure, with deformed universal joint connected in series, enables the robot head to do three kinds of movement. The scope of flexion and extension movement can reach±30o.The scope of rotary motion can reach±90o,and the scope of side flexion movement can reach±20o. On the basis of CAN bus, a distributed control system with simple structure, good real-time property and high reliability is designed.
     2. On the basis of bionics, a new kind of robot bionic olfactory system is put forward. This system has a nasal structure similar to that of human beings and an inspiratory system which functions as the human lungs do. It can simultaneously detect CO, SO2, H2S, O2 and one kind of volatile gas of organic compound. The adoption of electrochemistry and photoion gas sensors enables the system to recover quickly and choose correctly, so that the olfactory function of the robot is enormously improved. Moreover, it can conveniently adjust its gas sensor according to the target gas. The system adopts C8051F020 single chip microcomputer to realize the communication with the robot principal controller by means of serial port. With a compact structure, the performance of the system is unaffected by the installation position, so it can be assembled to other type of robots as a robot standardized component , in order to help the robot to complete the olfaction-related work.
     3. Inspired by the foraging strategies of animals, a strategy of odor source localization is put forward based on the animal predatory behavior. The strategy fuses the information of gas sensor, wind direction sensor and ultrasonic sensor etc. and integrates several good search algorithms such as Z-shaped search, upwind search and fuzzy neural network search and so on. In the strategy, the behavior-based containment control structure is adopted and a behavior module for various search algorithms is designed to enable the robot to select a better search strategy automatically in the course of seeking the odor source. The experimental results show that the strategy has strong robustness, and can meet the requirements of locating odor source in natural indoor environment.
     4. Drawing on the experience of human beings who also make use of other sense organs apart from the olfaction, this paper proposes a strategy to locate odor source by fusing the olfactory and visual information, and builds an odor source model base that is based on the information fusion of odor, color and distance, to facilitate robot to search and confirm the odor source. For this strategy, this paper designs a control system of the robot olfaction localization on the basis of multi-blackboard model. By seeking and confirming the odor source blackboard, the control system can coordinate the work to realize the odor source localization. Through experiments, this strategy is proved to posses the best efficiency, highest success rate and good ability to adjust to the environment.
引文
[1]李科杰.危险作业机器人发展战略研究.机器人技术及应用. 2003, (5): 14-22
    [2]王田苗.机器人技术与先进制造装备战略研究.机器人技术及应用. 2003, (5): 7-13
    [3]王栋耀,马旭东,戴先中.基于声纳的移动机器人沿墙导航控制,机器人. 2004, (4): 179-184
    [4]孟江华,朱纪洪,孙增圻.未知环境下基于传感器的移动机器人路径规划新方法.机器人. 2005, (4): 86-91
    [5]付宜利,顾晓宇,王树国.基于模糊控制的自主机器人路径规划策略研究.机器人. 2004, (6): 54-59
    [6]王敏,金·波斯科,黄心汉.基于传感器和模糊规则的机器人在动态障碍环境中的智能运动控.控制理论与应用. 2000, (6): 124-129
    [7]王越超.我国危险作业机器人研究开发取得新进展.机器人技术与应用. 2001, (3): 115-120
    [8]蔡自兴.智能控制及移动机器人研究进展.中南大学学报(自然科学版). 2005, (5): 108-113
    [9]王仁奎,李仲男,赵耀明等.反恐战士-广州卫富机器人.机器人技术与应用. 2003, (3): 61-64
    [10]胡传平.消防机器人的开发与应用.机器人技术与应用. 2003, (5): 147-152
    [11]肖永利,张琛.微型飞行器的研究现状与关键技术.宇航学报. 2001, (5): 38-42
    [12] Cui Genqun, Li Chunshu, Zhang Minglu. Kinematic Analysis of Mobile Manipulator for Measurement and Maintenance in Dangerous Environment. Journal of Wuhan University of Technology. 2006, 28(1): 983-988
    [13] Takanobu H, Takanishi A, Miwa H. Development of human-like head robots for modeling human mind and emotional human-robot interaction. The 3rd International Advanced Robotics Programme (IARP) Workshop on Humanoid and Human Friendly Robotics, Tsukuba, Japan. 2002: 104-109
    [14] Breazeal C. Emotion and sociable humanoid robots. International Journal of Human-Computer Studies. 2003, 59(1-2): 119-155
    [15] Breazeal C. Emotive qualities in robot speech. Proceedings of IEEE International Conference on Intelligent Robots and System, Seoul, Korea. 2001: 1389-1394
    [16] Breazeal C, Brooks A, Gray J. et al. Interactive Robot Theatre. Proceedings of 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, Taipei,Taiwan. 2003: 3648-3655
    [17] Miwa H, Umetsu T, Takanishi A, et al. human like robot head that has olfactory sensation and facial color expression. Proceedings of 2001 IEEE international conference on robotics and automation, Seoul, Korea. 2001: 459-464
    [18] Breazeal C, Scassellati B. Infant-like social interactions between a robot and a human caretaker. Adaptive Behavior. 2000, 8(1): 111-125
    [19] Breazeal C. Regulation and entrainment for human-robot interaction. International Journal of Experimental Robotics. 2002, 21(10-11): 883-902
    [20] Minsky M. Will robots inherit the Earth. Scientifical American. 1994(1): 87-91
    [21] Brooks R, Breazeal C, Marjanovic M, et al. The Cog project: building a humanoid robot. In: Computation for Metaphors, Analogy, and Agents, Springer-Verlag, Heidelberg. 1999: 52-87
    [22] Takanishi A, Ishimoto S, Matsuno T. Development of an Anthropomorphic head-eye System for Robot and Human Communication. Proceedings of 4th IEEE International Workshop on Robot and Human Communication (RO-MA’95), Tokyo, Japan. 1995: 77-82
    [23] Takanishi A, Matsuno T, Kato I. Development of an Anthropomorphic Head-Eye Robot with Two Eyes, Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Grenoble, France. 1997: 799-804
    [24] Miwa H, Umetsu T, Takanishi A, et al. human like robot head that has olfactory sensation and facial color expression. Proceedings of 2001 IEEE International Conference on Robotics and Automation, Seoul, Korea. 2001: 459-464
    [25] Miwa H, Umetsu T, Takanishi A, et al. Robot Personality based on the Equations of Emotion defined in the 3D Mental Space. Proceedings of the 2001 IEEE International Conference on Robotics and Automation, Seoul, Korea. 2001: 2602-2607
    [26] Miwa H. Humanlike head robot WE-3RV for emotional human-robot interaction. Fourteenth CISM-IFTOMM Symposium, Udine, Italy. 2002: 519-526
    [27] Miwa H, Okuchi T, Takanobu H, et al. Development of a new humanlike head robot WE-4. Proceedings of 2002 IEEE /RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland. 2002: 2443-2448
    [28] Miwa H. Okuchi T. Itoh K, et al. A New Mental Model for Humanoid Robots for Human Friendly Communication-Introduction of Learning System, Mood Vector and Second Order Equations of Emotion. Proceedings of the 2003 IEEE International Conference on Robotics and Automation, Taipei, Taiwan. 2003: 3588-3593
    [29] Patane F, Laschi C, Miwa H, et al. Design and development of a biologically-inspired artificial vestibular system for robot heads. Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systerns, Sendal, Japan. 2004: 1317-1322
    [30] Zecca M, Chaminade T, UmiltàM A, et al. Emotional Expression Humanoid Robot WE-4RII -Evaluation of the perception of facial emotional expressions by using fMRI. 2007 JSME Conference on Robotics and Mechatronics (ROBOMEC’07), Akita, Japan. 2007, A1-O10: 6-11
    [31] Kim H. Design of an Anthropomorphic Robot Head for Studying Autonomous Development and Learning. Proceedings. of the IEEE 2004 International Conference on Robotics and Automation, Sendal, Japan. 2004: 6-10
    [32] Berns K, Hirth J. Control of facial expressions of the humanoid robot head ROMAN. Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Rome, Italy. 2006:3119-3124
    [33] Hirth J, Berns K.Concept for Behavior Generation for the Humanoid Robot Head ROMAN based on Habits of Interaction.Proceedings of the IEEE-RAS International Conference on Humanoid Robots, Rome Italy. 2007:256-263
    [34] Hirth J, Schmitz N, Berns K. Emotional Architecture for the Humanoid Robot Head ROMAN. IEEE International Conference on Robotics and Automation (ICRA), Rome Italy. 2007: 2150-2155
    [35] Vijayakumar S, Souza A, Shibata T, et al. Statistical Learning for Humanoid Robots. Autonomous Robots. 2002, 12(1): 55-69
    [36] Kobayashi H, Ichikawa Y, Senda M, et al. Realization of realistic and rich facial expressions by face robot. Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, Nevada. 2003: 1123-1128
    [37]宋博等.机器人头部的视觉跟追系统研究.光学技术. 2003, 29(3): 347-353
    [38]姜明等.三自由度的侦察机器人系统.探测与控制学报. 2002, 24(3): 36-43
    [39]顾立忠,苏剑波.仿人机器人的头眼协调运动控制研究.机器人. 2008, 30(2): 165-170
    [40]冯威,陈工. 26自由度仿人机器人的设计与控制.机械工程与自动化. 2008, (2): 130-134
    [41] Wu Weiguo, Meng Qingmei. Development of the humanoid head portrait robot system with flexible face and expression. Proceedings of the 2004 IEEE International Conference on Robotics and Biomimetics, Shenyang, China. 2004: 718-723
    [42]鹿麟,吴伟国,孟庆梅.具有视觉及面部表情的仿人头像机器人系统设计与研制.机械设计, 2007, 24(7): 20-24
    [43]吴伟国,宋策,孟庆梅.仿人头像机器人”H&F robot-Ⅲ”语音及口形系统研制与实验.机械设计, 2008, 25(1): 15-19
    [44] Tsujita T, Konno A, Uchiyama M. Design and Development of a High Speed Binocular Camera Head [C].Proceedings of the 2005 IEEE International Conference on Robotics and Automation, Barcelona, Spain. 2005: 85-792
    [45] Mukai T,Onishi M,Odashima T,et al. Development of the Tactile Sensor System of a Human-Interactive Robot“RI-MAN”. IEEE Transactions on Robotics. 2008, 24(2): 505-512
    [46] Kikkawa Y, Yoko K, Matsuno T, et al. Discrimination of taste of amino acids with a multichannel taste sensor. Japanese journal of applied physics. 1993, (32): 5731-5736
    [47] Konyo M, Akazawa K, Tadokoro S, et al. Tactile Feel Display for Virtual Active Touch. Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems. Las Vegas, Nevada, 2003: 3744-3750
    [48] J S Elkinton, C Schal, T Ono, et al. Pheromone puff trajectory and upwind flight of male gypsy moths in a forest. Physiol Entomology. 1987, 12: 399-406
    [49] J. Atema. Eddy chemotaxis and odor landscapes: exploration of nature with animal sensors. Biol. Bull.,1996, 191:129-138
    [50] W Gardner. A brief history of electronic nose. Sensors and Actuators B. 1994, 18-19: 211-220
    [51] Rozas R, Morales J, Vega D. Artificial smell detection for robotic navigation. In: Fifth International Conference on Advanced Robotics. 1991: 1730-1733
    [52] Lilienthal A, Duckett T. A stereo electronic nose for a mobile inspection robot. In: ROSE’03. 1st International Workshop on Robotic Sensing. USA: IEEE. 2003: 1-6
    [53] Lilienthal A, Duckett T. Experimental Analysis of Smelling Braitenberg Vehicles. In: Proceedings of the IEEE International Conference on Advanced Robotics (ICAR 2003). Coimbra, Portugal. 2003: 39-43
    [54] Ahmed Mohamod Farah, Tom Duckett. Reactive localization of an odour source by a learning mobile robot. In: Proceedings of the Second Swedish Workshop on Autonomous Robotics. 2002: 29-38
    [55] Lilienthal A, Duckett T. Building gas concentration gridmaps with a mobile robot. Robotics and Autonomous Systems. 2004, 48(1): 3-16
    [56] Lilienthal A, Duckett T. Creating Gas Concentration Gridmaps with a Mobile Robot. In: Proceedings of the 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems. Las Vegas. Nevada, October, 2003: 118-123
    [57] Ishida H, Suetsugu K, Nakamoto T, et al. Study of autonomous mobile sensing system for localization of odor source using gas sensors and anemometric sensors. Sensors and Actuators A. 1994, 45(2) : 153-157
    [58] Ishida H, Kagawa Y, Nakamoto T, et al. Odor-source localization in clean room by autonomous mobile sensing system. In: Proceedings of the 1995 8th International Conference on Solid State Sensors and Actuators and Eurosensors IX. USA: IEEE. 1995: 783-786
    [59] Hiroshi Ishida, Gouki Nakayama, Takamichi Nakamoto, et al. Controlling a Gas/Odor Plume-Tracking Robot Based on Transient Responses of Gas Sensors. IEEE Sensors Journal. 2005, 5(3): 537-545
    [60] Hiroshi Ishida, Hidenao Tanaka, Haruki Taniguchi, et al. Mobile Robot Navigation Using Vision and Olfaction to Search for a Gas/Odor Source. In: Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2004, 1: 313-318
    [61] Hiroshi Ishida, Hidenao Tanaka, Haruki Taniguchi, et al. Mobile robot navigation using vision and olfaction to search for a gas/odor source. Auton Robot. 2006, 20:231-238
    [62] Hiroshi Ishida, Takamichi Nakamoto, Toyosaka Moriizumi. Remote sensing of gas/odor source location and concentration distribution using mobile system. Sensors and Actuators. 1998, B49: 52-57
    [63] Ishida H, Kobayashi A, Nakamoto T, et al. Three-dimensional odor compass. IEEE Transactions on Robotics and Automation. 1999, 15 (2): 251-257
    [64] R. Andrew Russell. An odour sensing robot draws inspiration from the insect world. In: 2nd International Conference on Bioelectromagnetism, February 1998 Melbourne AUSTRALIA. 1998: 49-50
    [65] Russell R A. Ant trails-an example for robots to follow. Proceedings IEEE In: International Conference on Robotics and Automation. 1999: 2698-2703
    [66] R. Andrew Russell. Locating Underground Chemical Sources by Tracking Chemical Gradients in 3 Dimensions. In: Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems. USA: IEEE, 2004: 325-330
    [67] Holland O, Melhuish C. Some adaptive movements of animats with single symmetrical sensors. In: Proceedings of the Fourth International Conference on Simulation of Adaptive Behaviour. Cambridge: M IT Press, 1996: 55-64
    [68] Russell R A. A Ground-Penetrating Robot for Underground Chemical Source Location. In: Proceeding of the international Conference on Intelligent Robots and Systems. 2005: 1879-1884
    [69] Pawel Pyk, Sergi Berm′udez i Badia, Ulysses Bernardet, et al. An artificial moth: Chemical source localization using a robot based neuronal model of moth optomotor anemotactic search.. Auton Robot. 2006, (20): 197-213
    [70] Gabbiani F, Krapp H G, Koch C, Laurent G. Multiplicative computation in a visual neuron sensitive to looming. Nature. 2002, 420(6913): 320-324
    [71] Sergi Bermúdez i Badia, Ulysses Bernardet, Alexis Guanella1, et al. A Biologically Based Chemo-Sensing UAV for Humanitarian Demining. International Journal of Advanced Robotic Systems. 2007, 4(2): 187-198.
    [72] Sergi Bermúdez i Badia1, Paul F.M.J. Verschure. Humanitarian Demining. I-Tech Education and Publishing, Vienna, Austria: 191-218
    [73] W. Li, J. A. Farrell, R. T. Cardé. Tracking of fluid-advected chemical plumes: Strategies inspired by insect orientation to pheromone. Adaptive Behavior.2001, 9: 143-170
    [74] W. Li, J. A. Farrell, S. Pang, et al. Moth-inspired chemical plume tracing on an autonomous underwater vehicle. IEEE Transactions on Robotics. 2006, 22(2): 292-307
    [75] J. A. Farrell, W. Li, S. Pang, et al. Chemical plume tracing experimental results with a REMUS AUV. In: Proc. of Ocean 2003 Marine Technology and Ocean Science Conference. 2003:962-978
    [76] J. A. Farrell, S. Pang, W. Li. Chemical plume tracing via an autonomous underwater vehicle. IEEE Journal of Ocean Engineering. 2005, 30:428-442
    [77] Ferri G, Caselli E, Mattoli V, et al. A biologically-inspired algorithm for gas/odor source localization in an indoor environment with no strong airflow: first experimental results. Proceedings of Workshop on Robotic Olfaction of IEEE International Conference on Robotics and Automation (ICRA). Roma, Italia, 2007
    [78] Ferri G, Caselli E, Mattoli V, et al. SPIRAL: A novel biologically-inspired algorithm for gas/odor source localization in an indoor environment with no strong airflow. Robotics and Autonomous Systems. 2008, 57(4): 393-402
    [79] Ferri G, Caselli E, Mattoli V, et al. Explorative particle swarm optimization method for gas/odor source localization in an indoor environment with no strong airflow. 2007 IEEE International Conference onRobotics and Biomimetics(ROBIO). 2007: 841-846
    [80] Michihisa Iida, Donghyeon Kang, Mitsuru Taniwaki, et al. Localization of CO2 source by a hexapod robot equipped with an anemoscope and a gas sensor. computers and electronics in agriculture. 2008, 63: 73-80
    [81] Hayes A T, Martinoli A, Goodman R M. Swarm robotic odor localization. In: Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems. USA: IEEE, 2001: 1073-1078
    [82] Hayes A T, Martinoli A, Goodman R M. Distributed odor source localization. IEEE Sensors Journal. 2002, 2 (3): 260-271
    [83] L Marques, U Nunes, A T de Almeida. Olfaction-based mobile robot navigation. Thin Solid Films. 2002, 418 (1): 51-58
    [84] L Marques, U Nunes, A T de Almeida. SpreadNose: Distributed agents for environmental monitoring. In P. Siciliano, editor, Sensors for Environmental Control, World Scientific. 2003: 234-238
    [85] Loutfi, A, Coradeschi, S, Karlsson L, et al. Putting olfaction into action: Using an electronic nose on a multi-sensing mobile robot. In: Proc. IEEE International Conference on Intelligent Robots and Systems (IROS). 2004: 337-342
    [86] Amy Loutfi, Mathias Broxvall, Silvia Coradeschi, et al. Object recognition: A new application for smelling robots. Robotics and Autonomous Systems. 2005, (52): 272-289
    [87] Amy Loutfi, Silvia Coradeschi. Smell, think and act: A cognitive robot discriminating odours. Auton Robot. 2006, (20): 239-249
    [88]李俊彩,孟庆浩,梁琼.基于进化梯度搜索的机器人主动嗅觉仿真研究.机器人. 2007, 29(3): 234-238
    [89]孟庆浩,李飞,张明路等.湍流烟羽环境下多机器人主动嗅觉实现方法研究.自动化学报. 2008, 34(10): 1281-1290
    [90] Qinghao Meng, Fei Li, Junwen Sun, et al. Multi-robot based odor source localization. RAS Newsletter– University of Waterloo. 2009, (7): 10-16.
    [91] Vickers N J, Baker T C. Reiterative responses to single strands of odor promote sustained upwind flight and odor source location by moth’s. Proceedings of the National Academy of Sciences. 1994, 91(10): 5756-5760
    [92] Lochmatter T, Raemy X, Matthey L, et al. A comparison of casting and spiraling algorithms for odor source localization in laminar flow, 2008 IEEE International Conference on Robotics and Automation(ICRA), Pasadena, CA. 2008: 1138-1143
    [93] Kuwana Y, Shimoyama I. A Pheromone-guided mobile robot that behaves like a silkworm moth with living antennae as pheromone sensors. The International Journal of Robotics Research. 1998, 17(9): 924–933
    [94] Kuwana Y, Shimoyama I, Sayama Y. Synthesis of pheromone-oriented emergent behavior of a silkwormmoth. In: Proceedings of the 1996 IEEE /RSJ International Conference on Intelligent Robots and Systems. USA: IEEE. 1996: 1722-1729
    [95] Balkovsky E, Shraiman B I. Olfactory search at high Reynolds number, Proceedings of the National Academy of Sciences, USA. 2002, 99(20): 12589-12593.
    [96] David J. Harvey. An investigation into insect chemical plume tracking using a mobile robot. Dissertation. Australia: The University of Adelaide South Australia. 2007
    [97] H Ishida, T Nakamoto, T Moriizumi. Remote sensing of gas/odor source location and concentration distribution using mobile system. Sensors and Actuators B. 1998, 49: 52-57
    [98] Crimaldi J P. The structure of passive scalar plumes in turbulent boundary layers. Proceedings of the 2nd International Symposium on Turbulence and Shear Flow Phenomena, Stockholm, Sweden. 2001: 115-120
    [99] Kuwana Y, Nagasawa, S, Shimoyama et al. Synthesis of the pheromone-oriented behaviour of silkworm moths by a mobile robot with moth antennae as pheromone sensors, Biosensors and Bioelectronics. 1999, 14(2): 195-202
    [100] Kanzaki R, Nagasawa S, Shimoyama I. Neural basis of odor-searching behavior in insect brain systems evaluated with a mobile robot. Chemical Senses, 2005, 30(1): 1285-1286
    [101] Rutkowski A, Edwards S, Willis M, et al. A Robotic platform for testing moth-inspired plume tracking strategies(ICRA). 2004: 3319-3324
    [102] Russell R A, Bab-Hadiashar A, Shepherd R L, et al. A Comparison of Reactive Robot Chemotaxis Algorithms. Robotics and Autonomous Systems. 2003, 45: 83-97
    [103] Grasso F, Atema J. Integration of ?ow and chemical sensing for guidance of autonomous marine robots in turbulent ?ows. Environmental Fluid Mechanics. 2002, 2: 95-114
    [104] Sandini G, Lucarini G, Varoli M, et al. Gradient driven selforganising systems. Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 1993: 1941-1943
    [105] Kazadi S, Goodman R, Tsikata D, et al. An autonomous water vapor plume tracking robot using passive resistive polymer sensors. Autonomous Robots. 2006, 9(2): 175–188
    [106] Martinez D. A biomimetic robot for tracking specific odors in turbulent plumes. Autonomous Robot. 2006, 20: 185–195
    [107] Cyrill Stachniss, Christian Plagemann, Achim Lilienthal. Gas Distribution Modeling using Sparse Gaussian Process Mixture Models. Autonomous Robots. 2009, 26(2-3): 187-202
    [108] Gabriele Ferri, Michael V, Jakuba, Emanuele Caselli. Localizing Multiple Gas/Odor Sources in an Indoor environment using Bayesian Occupancy Grid Mapping. Proceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, San Diego, CA, USA. 2007: 566-571
    [109] Achim Lilienthal, Amy Loutfi, Jose Luis Blanco, et al. Integrating SLAM into Gas Distribution Mapping. IEEE International Conference on Robotics and Automation (ICRA) Workshop on“RoboticOlfaction– Towards Real Applications”, Rome, Italy. 2007: 21-28
    [110] Vergassola M, Villermaux E, Shraiman, B. 'Infotaxis' as a strategy for searching without gradients. Nature. 2007, 445:406-409
    [111]黎介寿,吴孟超,黄志强.普通外科手术学.第二版.北京:人民军医出版社, 2005
    [112]丁自海.人体解剖学.北京:中国协和医科大学出版社, 2007
    [113]赵建东,邵黎君,徐凯,等.基于CAN总线的仿人机器人关节伺服控制系统研究.机器人. 2002, 24(5): 421-426
    [114]安秋,姬长英,周俊,等.基于CAN总线的农业移动机器人分布式控制网络.农业机械学报. 2008, 39(6): 123-117
    [115]王磊,曲建岭,杨建华.发展中的电子鼻技术.测控技术. 1999, 18(5): 8-10
    [116]王光大,朱坤,徐进.人体嗅觉系统模拟的研究.仪器仪表学报. 2006, 27(6): 80-81
    [117] David J. Harvey. An Investigation Into Insect Chemical Plume Tracking Using a Mobile Robot. Dissertation. Australia: The University of Adelaide South Australia. 2007
    [118]鲍可进. C8051F单片机原理及应用.北京:中国电力出版社, 2006
    [119]胡茜,葛思擘,王伊卿,李伟.电化学气敏传感器的原理及其应用.仪表技术与传感器. 2007, (5):77-78
    [120]史雪飞,冯淑红. DS1820芯片在电化学传感器温度补偿中的应用.工业计量. 2006, 2(1): 1-14
    [121]李国玉,孙以材,潘国峰.基于网络的压力传感器信息融合.仪器仪表学报. 2005, 26(2): 168-171
    [122] Simon Haykin.神经网络原理.叶世伟,史忠植,译.北京:机械工业出版社, 2004.
    [123]刘伟军,董再励.基于立体视觉的移动机器人自主导航定位系统.高技术通讯. 2001, 11(70): 91-94
    [124]沈艳涛,于建国.有毒有害气体泄漏的CFD数值模拟-模型建立与校验.化工学报. 2007, 58(3): 745-749
    [125]蔡风英,谈宗山,孟赫,等.化工安全工程.北京:科学出版社, 2001
    [126]王文娟,刘剑锋.危险性气体泄漏扩散数学模拟研究.工业安全与环保. 2006, 32(11): 23-25
    [127]周波,张国枢..有害物质泄漏扩散的数值模拟.工业安全与环保. 2005, 31(10): 42-44
    [128]张雷斌.常州高新区重气泄漏、扩散反演.硕士学位论文.北京:中国地质大学, 2007
    [129]王福军.计算流体动力学分析-CFD软件原理与应用.北京:清华大学出版社, 2004
    [130]汪定伟,王俊伟,王洪峰,等.智能优化方法.北京:高等教育出版社, 2007
    [131] Linhares A. State-space search strategies gleaned from Animal behavior: a traveling salesman experiment. Biological Cybernetics. 1998, 78(3): 167-173
    [132] Linhares A. Synthesizing a predatory search strategy for VLSI layouts. IEEE Transactions on Evolutionary Computation. 1999, 3(2): 147-152
    [133] Brooks R A. A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation. 1986, RA22 (1) : 14-23
    [134]陈小娇,杨先一,金文标.基于行为模糊控制的机器人绕墙走研究.微计算机信息. 2008, 24(5-2): 242-244
    [135]孙增圻,张再兴,邓志东.智能控制理论与技术.北京:清华大学出版社, 1997
    [136]郭兰申.面向反恐领域基于多源信息融合的机器人感知系统研究.博士学位论文.天津:河北工业大学, 2006
    [137]刘兴荣.用于移动机器人的双目立体视觉技术.硕士学位论文.天津:河北工业大学, 2003.
    [138]管业鹏,童林夙.双目立体视觉测量方法研究.仪器仪表学报. 2003, 24(6): 581-584.
    [139]李自力,朱光喜,耀庭.一种基于会聚双目立体视觉的用户化身模型.电子与信息学报. 2003, 6(25): 763-711.
    [140]王建华,韩红艳,王春平,朱元昌. CCD双目立体视觉测量系统的理论研. 2007, 4(14): 94-96.
    [141]朱效明,高稚允.双CCD立体视觉系统的理论研究.光学技术. 2003, 29(3) : 298-300.
    [142]刘江华,陈佳品,程君实.双目视觉平台的研究.机器人技术与应用. 2002, (1): 36- 40.
    [142]邢怀学,朱旻,浦玉强,等.基于双目立体视觉的三维地形重构.地理与地理信息科学. 2007, 23(2): 2-3
    [143]肖占春.基于双目立体视觉的机器人导航研究.硕士学位论文.沈阳:东北师范大学, 2008
    [144]林琳.基于双目立体视觉的AGV导航技术研究.硕士学位论文.西安:西安理工大学, 2007
    [145]刘相滨,邹北骥,孙家广.基于边界跟踪的快速欧氏距离变换算法.计算机学报. 2006, 29(2): 317-323
    [146]章毓晋.图像工程(上):图像处理.北京:清华大学出版社, 2006
    [147] Llinas J, et al. Blackboard concepts for data fusion applications. Inter. Journal of Pattern Recognition and AI. 1993, 7 (2) :285-308
    [148]于存贵,李自勇,马志文.基于黑板模型的多属性决策模式.南京理工大学学报. 2000, 24(4): 334-337
    [149]韩伟,韩忠愿.基于黑板模型的多智能体合作学习.计算机工程. 2007, 33(22):42-47

© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号

地址:北京市海淀区学院路29号 邮编:100083

电话:办公室:(+86 10)66554848;文献借阅、咨询服务、科技查新:66554700