Human-Manipulator Interface Using Hybrid Sensors via CMAC for Dual Robots
AbstractThis paper presents a novel method that allows a human operator to communicate his motion to the dual robot manipulators by performing his two double hand-arms movements, which would naturally carry out an object manipulation task. The proposed method uses hybrid sensors to obtain the position and orientation of the human hands. Although the position and the orientation of the human can be obtained from the sensors, the measurement errors increase over time due to the noise of the devices and the tracking error. A cerebellar model articulation controller (CMAC) is used to estimate the position and orientation of the human hand. Due to the limitations of the perceptive and the motor, human operator can not accomplish the high precision manipulation without any assistant. An adaptive multi-space transformation (AMT) is employed to assist the operator to improve the accuracy and reliability in determining the pose of the manipulator. With making full use of the human hand-arms motion, the operator would feel kind of immersive. Using this human-robot interface, the object manipulation task done in collaboration by dual robots could be carried out flexibly through preferring the double hand-arms motion by one operator.
T. Ando, R. Tsukahara, M. Seki (2012); A Hapic Interface Force Blinker 2 for Navigation of the Visually Impaired, IEEE Trans. on Industrial Electronics, 59(11): 4112-4119. http://dx.doi.org/10.1109/TIE.2011.2173894
K. Kiguchi, S. Kariya, K. Watanabe (2003); An exoskeletal robot for human elbow motion supportsensor fusion, adaptation, and control, IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics, 31(3): 353-361.
GL. Du, P. Zhang, LY. Yang, YB. Su (2010); Robot teleoperation using a vision-based manipulation method, Audio Language and Image Processing, (ICALIP 2010 Int. Conf., Shanghai, 945-949.
A. Peer, H. Pongrac, M. Buss (2010); Influence of Varied Human Movement Control on Task Performance and Feeling of Telepresence, Presence-Teleoperators and Virtual Environments, 19(5):463-481. http://dx.doi.org/10.1162/pres_a_00007
V. Siddharth (2004); Vision-based markerless 3D human-arm tracking, M.A.Sc. Thesis, Dept. of Mech. Eng., University of Ottawa, Canada.
YH Ma, ZH Mao, W. Jia, C. Li, J. Yang, Magnetic Hand Tracking for Human-Computer Interface, IEEE Trans. on Magnetics, 47(5): 970-973, 2011. http://dx.doi.org/10.1109/TMAG.2010.2076401
K.C.C. Peng, W. Singhose, D.H.Frakes (2012); Hand-Motion Crane Control Using Radio-Frequency Real-Time Location Systems, IEEE Trans. on Mechatronics, 17(3): 464-471.
M. Khezri, M. Jahed (2011); A Neuro Fuzzy Inference System for sEMG-Based Identification of Hand Motion Commands, IEEE Trans. on Industrial Electronics, 58(5): 1952-1960. http://dx.doi.org/10.1109/TIE.2010.2053334
A.R.Varkonyi-Koczy, B.Tusor (2011); HumanComputer Interaction for Smart Environment Applications Using Fuzzy Hand Posture and Gesture Models, IEEE Transactions on Instrumentation and Measurement, 60(5):1505-1514. http://dx.doi.org/10.1109/TIM.2011.2108075
B. Ionescu, D. Coquin, P. Lambert, V. Buzuloiu (2005); Dynamichand gesture recognition using the skeleton of the hand, Journal on Applied Signal Processing, 2101-2109.
GL Du, P Zhang (2014); Markerless Human-Robot Interface for Dual Robot Manipulators Using Kinect Sensor, Robotics and Computer Integrated Manufacturing, 30(2): 150-159. http://dx.doi.org/10.1016/j.rcim.2013.09.003
J. Kofman, S. Verma, X. Wu (2007); Robot-Manipulator Teleoperation by Markerless Vision-Based Hand-Arm Tracking, Int. J. of Optomechatronics, 1(3): 331-357.
R. Marin, PJ. Sanz, R. Wirz (2005); A Multimodal Interface to Control a Robot Arm via theWeb: A Case Study on Remote Programming, IEEE Transactions on Industrial Electronics, 52(6): 1506-1521. http://dx.doi.org/10.1109/TIE.2005.858733
CM. Lin, LY. Chen, DS. Yeung (2010); Adaptive Filter Design Using Recurrent Cerebellar Model Articulation Controller, IEEE Trans. on Neural Networks, 19(7): 1149-1157.
X. Yun, ER. Bachmann, RB. McGhee (2008): A Simplified Quaternion-Based Algorithm for Orientation Estimation From Earth Gravityand Magnetic Field Measurements, IEEE Trans. on Instrumentation and Measurement, 57(3): 638-650. http://dx.doi.org/10.1109/TIM.2007.911646
LM. Munoz, A. Casals (2009); Improving the Human-Robot Interface Through Adaptive Multispace Transformation, IEEE Trans. on Robotics, 25(5): 1208-1213.
Improving the Human-Robot Interface Through Adaptive Multispace Transformation, IEEE Trans. on Robotics, 25(5): 1208-1213. http://dx.doi.org/10.1109/TRO.2009.2024790
G. Antonelli, S.Chiaverini, G. Fusco (2003); A new on-line algorithm for inverse kinematics of robot manipulators ensuring path tracking capability under joint limits, IEEE Trans. on Robotics and Automation, 19(1): 162-167. http://dx.doi.org/10.1109/TRA.2002.807543
R. Marin, PJ. Sanz, R.Wirz (2005); A Multimodal Interface to Control a Robot Arm via the Web: A Case Study on Remote Programming, IEEE Trans. on Industrial Electronics, 52(6): 1506-1521. http://dx.doi.org/10.1109/TIE.2005.858733
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