轮式移动机器人避障的研究
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摘要
本文使用了超声波传感器对移动机器人周围的环境进行探测，并且利用单片机技术对超声波传感器所探得的障碍物信息进行处理，最终通过一种新颖的模糊神经控制算法来完成障碍物的模式识别，从而实现了移动机器人的自主避障。其具体内容如下所示:
采用8个US系列的BTE054超声波传感器对移动机器人周围的环境信息进行采集，并且利用含有日本日立公司生产的SH7044(QFP-112Pin)芯片的单片机对采集到的环境信息进行处理。为了增加单个超声波传感器的测量精度和减小多个超声波传感器所产生的干涉现象，在硬件上采取了多个传感器复数统接的方法，在软件上使用了均值法和智能预测法。
本文还提出了一种新颖的模式识别算法用于移动机器人的自主避障。通过应用一定量的模糊规则与FKCN（模糊Kohonen聚类网络）的结合，生成了一种启发式的模糊神经网络，并且通过对该模糊神经网络进行离线的非监督式训练，建立起了超声波传感器输入信号和移动机器人速度之间的模式映射关系，从而实现了移动机器人连续、快速的避障。
最后，为了验证以上方法的可行性，通过Visual C++编程软件在计算机上作了各种避障情况的仿真，同时也在室内进行了各种实物避障的实验。
To realize the autonomous obstacle avoidance of mobile robots, a series of methods are presented in this paper, which include circumstance detection around a mobile robot by ultrasonic sensors, obstacle input data process through microcomputer techniques and pattern recognition of obstacles with a fuzzy-neuro control algorithm. It mainly involves the following works:
Circumstance data acquisition is accomplished by 8 US series BTE054 ultrasonic sensors , and circumstance input data process is completed through a microcomputer embedded with a Japanese Hitachi SH7044(QFP-112Pin)chip. In order to increase the measurement precision of single ultrasonic sensor and decrease the interference degree produced by multiple ultrasonic sensors, this paper provides a hardware method called multi-connection, and two software ways named median and intelligent forecast.
This paper also presents a novel pattern recognition algorithm that is used to achieve autonomous obstacle avoidance of a mobile robot. Through the combination of heuristic fuzzy rules and the Kohonen clustering network, a heuristic fuzzy-neuro network is developed. This method also builds up pattern-mapping between ultrasonic sensory input data and velocity command by applying the off-line and unsupervised training method to this network, allowing continuous, fast motion for obstacle avoidance.
In order to verify the effectiveness of these proposed methods, this paper finally gives the results of all kinds of obstacle avoidance simulation in a computer virtual environment with Visual C++ and also presents wealthy real experiments indoors.
采用8个US系列的BTE054超声波传感器对移动机器人周围的环境信息进行采集，并且利用含有日本日立公司生产的SH7044(QFP-112Pin)芯片的单片机对采集到的环境信息进行处理。为了增加单个超声波传感器的测量精度和减小多个超声波传感器所产生的干涉现象，在硬件上采取了多个传感器复数统接的方法，在软件上使用了均值法和智能预测法。
本文还提出了一种新颖的模式识别算法用于移动机器人的自主避障。通过应用一定量的模糊规则与FKCN（模糊Kohonen聚类网络）的结合，生成了一种启发式的模糊神经网络，并且通过对该模糊神经网络进行离线的非监督式训练，建立起了超声波传感器输入信号和移动机器人速度之间的模式映射关系，从而实现了移动机器人连续、快速的避障。
最后，为了验证以上方法的可行性，通过Visual C++编程软件在计算机上作了各种避障情况的仿真，同时也在室内进行了各种实物避障的实验。
To realize the autonomous obstacle avoidance of mobile robots, a series of methods are presented in this paper, which include circumstance detection around a mobile robot by ultrasonic sensors, obstacle input data process through microcomputer techniques and pattern recognition of obstacles with a fuzzy-neuro control algorithm. It mainly involves the following works:
Circumstance data acquisition is accomplished by 8 US series BTE054 ultrasonic sensors , and circumstance input data process is completed through a microcomputer embedded with a Japanese Hitachi SH7044(QFP-112Pin)chip. In order to increase the measurement precision of single ultrasonic sensor and decrease the interference degree produced by multiple ultrasonic sensors, this paper provides a hardware method called multi-connection, and two software ways named median and intelligent forecast.
This paper also presents a novel pattern recognition algorithm that is used to achieve autonomous obstacle avoidance of a mobile robot. Through the combination of heuristic fuzzy rules and the Kohonen clustering network, a heuristic fuzzy-neuro network is developed. This method also builds up pattern-mapping between ultrasonic sensory input data and velocity command by applying the off-line and unsupervised training method to this network, allowing continuous, fast motion for obstacle avoidance.
In order to verify the effectiveness of these proposed methods, this paper finally gives the results of all kinds of obstacle avoidance simulation in a computer virtual environment with Visual C++ and also presents wealthy real experiments indoors.
引文
1 徐国华, 谭民.移动机器人的发展现状及其趋势.机器人技术与应用,2001,3:5-16
2 刘凤然, 田红芳, 王侃.基于单片机的移动机器人自动避障控制系统.中国仪器仪表,2001,3:27-29
3 李庆中, 顾伟康, 叶秀清.基于遗传算法的移动机器人动态避障路径规划方法.模式识别与人工智能,2002,15(2):161-166
4 Charles.C.Chan, K.T.Song.Ultrasonic Sensor Data Integration and Its Application to Environment Perception.Journal of Robotic Systems,1996,13(10): 663-677
5 A.Elfes.Sonar-Based Real-World Mapping and Navigation.IEEE Trans.Robotics and Automation,1978,3(3):249-265
6 A.Zelinsky.Mobile Robot Map Making Using Sonar.J. Robotic Systems,1991,8(5): 557-577
7 J.L.Crowley.World Modeling and Position Estimation for A Mobile Robot Using Ultrasonic Ranging.Proc.IEEE int.Conf.Robotics and Automation,Scottsdale,AZ, 1989:674-680
8 J.Borenstein, Y.Koren.Obstacle Avoidance Using Ultrasonic Sensors.IEEE Trans. Robotics and Automation,1988,4(2):213-218
9 Daehee Kang, R.C.Luo.Position Estimation for Mobile Robot Using Sensor Fusion. Proc.IEEE Conf.on Multisensor Fusion and Integration for Intelligent System,1994, 10:647-652
10 J.Borenstein, Y.Koren.The Vector Field Histogram-Fast Obstacle Avoidance for Mobile Robot.IEEE Trans.Robotics Automat,1991,7(3):278-288
11 J.Borenstein, Y.Koren.Real-Time Obstacle Avoidance for Fast Mobile Robots.IEEE Trans.Systems Man and Cybernetics,1989,19(5):1179-1187
12 J.Borenstein, Y.Koren.Histogramic In-Motion Mapping for Mobile Robot Obstacle Avoidance.IEEE Trans.Robotics and Automation,1991,7(4):535-539
13 Bertrand, Beaufrere, S.Zeghloul.A Mobile Robot Navigation Method Using A Fuzzy Logic Approach.Robotica,1995,13:437-448
艾海舟, 郝放, 刘文, 等.基于人工神经网络的移动机器人研究.机器人,
14 1995,17(1):32-35
15 L.H.Suh, T.W.Onkim.Fuzzy Membership Function Based Networks with Application to The Visual Serving of Robot Manipulators.IEEE Transactions on Fuzzy Systems,1994,2(3):203-220
16 J.Z.Liu, W.X Xie.Pyramid Segmentation of Color Images Using Fuzzy-C Means Cluster Algorism.In:Proceedings of 1993 IEEE Region 10 Conference Computer Commune Control Power Engine,1993.1130-1131
17 H.G.Tillema.An Overview of The Mobile Autonomous Robot Twente Project. University Twente,MART,1993
18 H.Makino, T.Arai.New Developments in Assembly Systems. Annals of the CIRP, 1994,43:112-119
19 黄贤武.传感器实际应用电路设计.成都:电子科技大学出版社,1997:200-209
20 何希才.传感器及其应用电路.北京:电子工业出版社,2001:146-161
21 李科杰.传感技术.北京:北京理工大学出版社,1989:110-120
22 R.A.Jarvis.A Perspective on Range Finding Techniques for Computer Vision. IEEE Trans. Pattern Anal,1983,5(2):122-139
23 S.F.EI Hakim, N.j.Pizzi.Multi-Camera Vision-Based Approach to Flexible Feature Measurement for Inspection and Reverse Engineering. Optical Eng,1993,32(9): 80-93
24 M.Yang, H.Wang, K.He.Obstacle Avoidance Using Range Data in Autonomous Navigation of Mobile Robot. WenTd. Proc of the 1999 International Symposiumon Test and Measurement.Xi'an:Int Academic Publishers,1999,929-933.
25 C.C.Chu, J.K.Aggarwal.Image Interpretation Using Multiple Sensing Modalities. IEEE Trans. PAMI,1992,14(8):840-646
26 陈维明, 陈维南, 冯纯伯.视觉和超声波信息的融合与机器人伺服控制的研究.机 器人,1994(1):8-13
27 张立勋.机械电子学.哈尔滨:哈尔滨工程大学出版社,1999:153-172
28 周航慈.单片机应用程序设计技术.北京:北京航空航天大学出版社,1991:127-136
29 刘乐善.微型计算机接口技术.成都:电子科技大学出版社,1994:95-120
30 R.C.Arkin.Motor Schema-Based Mobile Robot Navigation.The International Journal of Robotics Reasearch,1989,8(4):92-112
R.C.Arkin.Intergrating behavioral.Perceptual and World Knowledge in Reactive
31 Navigation.Robotics and Autonomous Systems,1990,6:105-122
32 R.A.Brooks.A Robust Layered Control System for A Mobile Robot.IEEE Journal on Robotics and Automation RA-2,1986,1.
33 Y.J.Kim, J.H.Kim, D.S.Kwon.Evolutionary Programming-Based Uni-Vector Field Navigation Method for Fast Mobile Robots.IEEE Transactions on Systems Man and Cybernetics,2001,31(3):450-458
34 L.A.Zadeh.Fuzzy Sets.Information and Control,1965(8):338-353
35 徐叙华.模糊逻辑与模糊推理.成都:西南交通大学出版社,1989:145-156
36 沈百英.数理逻辑.长沙:国防工业出版社,1991:12-40
37 何新贵.模糊知识处理的理论与技术.长沙:国防工业出版社,1994:50-70
38 S.Grossberg.Studies of Mind and Brain.Boston,1982
39 廖晓昕.细胞神经网络的数学理论.中国科学,1994,24(9):902-910
40 L.O.Chua, L.Yang.Cellular Neural Network.IEEE Trans,1988,35(10):1257-1272
41 曹焕光.人工神经元网络原理.北京:气象出版社,1992:50-70
42 B.Kosko.Neural Networks and Fuzzy Systems.Pretice-Hall,Englewood Cliff,1992
43 P.J.Werbos.Neural Control and Fuzzy Logic:Connection and Design.Proc.of UCNN,1991
44 C.T.Lin.Neural-Network-Based Fuzzy Logic Control and Design System.IEEE Trans.Computer,1991,40(12)
45 B.Kosko.Neural Networks and Fuzzy Systems: a Dynamic Approach to Intelligence. NJ: Prentice-Hall,1992
46 A.Blanco, M.I.Requena.Improved Fuzzy Neural Networks for Solving Relational Equations.Fuzzy Sets and Systems,1995,72:311-322
47 H.Ishibuchi, H.Tanaka.A Learning Algorithm Fuzzy Neural Networks with Triangular Fuzzy Weights.Fuzzy Sets and Systems,1995,71:277-293
48 J.J.Buckley, Y.Hayashi.Fuzzy Neural Networks: A Survey. Fuzzy Sets and Systems, 1994,66:1-13
49 张明路, 彭商贤, 曹作良, 等.用于移动机器人避障的人工神经网络和模糊逻辑控制技术.中国机械工程,1997,8(2):21-24
M.Benreguieg, Ph.Hoppenot, H.Maaref.Fuzzy Navigation Strategy:Application to Two
50 Distinct Autonomous Mobile Robots.Robotica,1997,15:609-615
51 J.C. Bezdek.Fuzzy Models for Pattern Recognition. New York:IEEE Press,1992
52 T.Huntsberger, P.Ajjimarangsee.Parallel Self-Organizing Feature Maps for Unsupervised Pattern Recognition.Intentional J.General Systems 1990,16(4): 357-372
53 T.Kohonen.Self-Organizing Maps.London:Springer,1997
54 冯辛安, 葛巧琴.CAD/CAM技术概论.北京:机械工业出版社,1995:1-8
55 杨雄飞, 魏刚.计算机辅助设计.北京:机械工业出版社,1998:1-9
56 黄维通.Visual C++面向对象与可视化程序设计.北京:清华大学出版社,2000:20-67
57 邓良松.软件工程.西安:西安电子科技大学出版社,2000:34-67
58 谭浩强.C程序设计.北京:清华大学出版社,1991:52-72
59 T.Arai.The Control and Application of Omni-Driectional Vehicle. Proceedings of 8th World Congress of IFAC ,1981(4):1855-1860
60 E.Nakano.An Advanced Mechanism of the Omni-Directional Vehicle (ODV)and Its Application to the Working Wheelchair for the Disabled.Proc.'83 ICAR,1983: 277-284
61 B.Carlisle.An Omni-Directional Mobile Robot.Developments in Robotics,1983: 79-87
2 刘凤然, 田红芳, 王侃.基于单片机的移动机器人自动避障控制系统.中国仪器仪表,2001,3:27-29
3 李庆中, 顾伟康, 叶秀清.基于遗传算法的移动机器人动态避障路径规划方法.模式识别与人工智能,2002,15(2):161-166
4 Charles.C.Chan, K.T.Song.Ultrasonic Sensor Data Integration and Its Application to Environment Perception.Journal of Robotic Systems,1996,13(10): 663-677
5 A.Elfes.Sonar-Based Real-World Mapping and Navigation.IEEE Trans.Robotics and Automation,1978,3(3):249-265
6 A.Zelinsky.Mobile Robot Map Making Using Sonar.J. Robotic Systems,1991,8(5): 557-577
7 J.L.Crowley.World Modeling and Position Estimation for A Mobile Robot Using Ultrasonic Ranging.Proc.IEEE int.Conf.Robotics and Automation,Scottsdale,AZ, 1989:674-680
8 J.Borenstein, Y.Koren.Obstacle Avoidance Using Ultrasonic Sensors.IEEE Trans. Robotics and Automation,1988,4(2):213-218
9 Daehee Kang, R.C.Luo.Position Estimation for Mobile Robot Using Sensor Fusion. Proc.IEEE Conf.on Multisensor Fusion and Integration for Intelligent System,1994, 10:647-652
10 J.Borenstein, Y.Koren.The Vector Field Histogram-Fast Obstacle Avoidance for Mobile Robot.IEEE Trans.Robotics Automat,1991,7(3):278-288
11 J.Borenstein, Y.Koren.Real-Time Obstacle Avoidance for Fast Mobile Robots.IEEE Trans.Systems Man and Cybernetics,1989,19(5):1179-1187
12 J.Borenstein, Y.Koren.Histogramic In-Motion Mapping for Mobile Robot Obstacle Avoidance.IEEE Trans.Robotics and Automation,1991,7(4):535-539
13 Bertrand, Beaufrere, S.Zeghloul.A Mobile Robot Navigation Method Using A Fuzzy Logic Approach.Robotica,1995,13:437-448
艾海舟, 郝放, 刘文, 等.基于人工神经网络的移动机器人研究.机器人,
14 1995,17(1):32-35
15 L.H.Suh, T.W.Onkim.Fuzzy Membership Function Based Networks with Application to The Visual Serving of Robot Manipulators.IEEE Transactions on Fuzzy Systems,1994,2(3):203-220
16 J.Z.Liu, W.X Xie.Pyramid Segmentation of Color Images Using Fuzzy-C Means Cluster Algorism.In:Proceedings of 1993 IEEE Region 10 Conference Computer Commune Control Power Engine,1993.1130-1131
17 H.G.Tillema.An Overview of The Mobile Autonomous Robot Twente Project. University Twente,MART,1993
18 H.Makino, T.Arai.New Developments in Assembly Systems. Annals of the CIRP, 1994,43:112-119
19 黄贤武.传感器实际应用电路设计.成都:电子科技大学出版社,1997:200-209
20 何希才.传感器及其应用电路.北京:电子工业出版社,2001:146-161
21 李科杰.传感技术.北京:北京理工大学出版社,1989:110-120
22 R.A.Jarvis.A Perspective on Range Finding Techniques for Computer Vision. IEEE Trans. Pattern Anal,1983,5(2):122-139
23 S.F.EI Hakim, N.j.Pizzi.Multi-Camera Vision-Based Approach to Flexible Feature Measurement for Inspection and Reverse Engineering. Optical Eng,1993,32(9): 80-93
24 M.Yang, H.Wang, K.He.Obstacle Avoidance Using Range Data in Autonomous Navigation of Mobile Robot. WenTd. Proc of the 1999 International Symposiumon Test and Measurement.Xi'an:Int Academic Publishers,1999,929-933.
25 C.C.Chu, J.K.Aggarwal.Image Interpretation Using Multiple Sensing Modalities. IEEE Trans. PAMI,1992,14(8):840-646
26 陈维明, 陈维南, 冯纯伯.视觉和超声波信息的融合与机器人伺服控制的研究.机 器人,1994(1):8-13
27 张立勋.机械电子学.哈尔滨:哈尔滨工程大学出版社,1999:153-172
28 周航慈.单片机应用程序设计技术.北京:北京航空航天大学出版社,1991:127-136
29 刘乐善.微型计算机接口技术.成都:电子科技大学出版社,1994:95-120
30 R.C.Arkin.Motor Schema-Based Mobile Robot Navigation.The International Journal of Robotics Reasearch,1989,8(4):92-112
R.C.Arkin.Intergrating behavioral.Perceptual and World Knowledge in Reactive
31 Navigation.Robotics and Autonomous Systems,1990,6:105-122
32 R.A.Brooks.A Robust Layered Control System for A Mobile Robot.IEEE Journal on Robotics and Automation RA-2,1986,1.
33 Y.J.Kim, J.H.Kim, D.S.Kwon.Evolutionary Programming-Based Uni-Vector Field Navigation Method for Fast Mobile Robots.IEEE Transactions on Systems Man and Cybernetics,2001,31(3):450-458
34 L.A.Zadeh.Fuzzy Sets.Information and Control,1965(8):338-353
35 徐叙华.模糊逻辑与模糊推理.成都:西南交通大学出版社,1989:145-156
36 沈百英.数理逻辑.长沙:国防工业出版社,1991:12-40
37 何新贵.模糊知识处理的理论与技术.长沙:国防工业出版社,1994:50-70
38 S.Grossberg.Studies of Mind and Brain.Boston,1982
39 廖晓昕.细胞神经网络的数学理论.中国科学,1994,24(9):902-910
40 L.O.Chua, L.Yang.Cellular Neural Network.IEEE Trans,1988,35(10):1257-1272
41 曹焕光.人工神经元网络原理.北京:气象出版社,1992:50-70
42 B.Kosko.Neural Networks and Fuzzy Systems.Pretice-Hall,Englewood Cliff,1992
43 P.J.Werbos.Neural Control and Fuzzy Logic:Connection and Design.Proc.of UCNN,1991
44 C.T.Lin.Neural-Network-Based Fuzzy Logic Control and Design System.IEEE Trans.Computer,1991,40(12)
45 B.Kosko.Neural Networks and Fuzzy Systems: a Dynamic Approach to Intelligence. NJ: Prentice-Hall,1992
46 A.Blanco, M.I.Requena.Improved Fuzzy Neural Networks for Solving Relational Equations.Fuzzy Sets and Systems,1995,72:311-322
47 H.Ishibuchi, H.Tanaka.A Learning Algorithm Fuzzy Neural Networks with Triangular Fuzzy Weights.Fuzzy Sets and Systems,1995,71:277-293
48 J.J.Buckley, Y.Hayashi.Fuzzy Neural Networks: A Survey. Fuzzy Sets and Systems, 1994,66:1-13
49 张明路, 彭商贤, 曹作良, 等.用于移动机器人避障的人工神经网络和模糊逻辑控制技术.中国机械工程,1997,8(2):21-24
M.Benreguieg, Ph.Hoppenot, H.Maaref.Fuzzy Navigation Strategy:Application to Two
50 Distinct Autonomous Mobile Robots.Robotica,1997,15:609-615
51 J.C. Bezdek.Fuzzy Models for Pattern Recognition. New York:IEEE Press,1992
52 T.Huntsberger, P.Ajjimarangsee.Parallel Self-Organizing Feature Maps for Unsupervised Pattern Recognition.Intentional J.General Systems 1990,16(4): 357-372
53 T.Kohonen.Self-Organizing Maps.London:Springer,1997
54 冯辛安, 葛巧琴.CAD/CAM技术概论.北京:机械工业出版社,1995:1-8
55 杨雄飞, 魏刚.计算机辅助设计.北京:机械工业出版社,1998:1-9
56 黄维通.Visual C++面向对象与可视化程序设计.北京:清华大学出版社,2000:20-67
57 邓良松.软件工程.西安:西安电子科技大学出版社,2000:34-67
58 谭浩强.C程序设计.北京:清华大学出版社,1991:52-72
59 T.Arai.The Control and Application of Omni-Driectional Vehicle. Proceedings of 8th World Congress of IFAC ,1981(4):1855-1860
60 E.Nakano.An Advanced Mechanism of the Omni-Directional Vehicle (ODV)and Its Application to the Working Wheelchair for the Disabled.Proc.'83 ICAR,1983: 277-284
61 B.Carlisle.An Omni-Directional Mobile Robot.Developments in Robotics,1983: 79-87