Abstract
Controlling a tendon-driven robot like the humanoid Ecce is a difficult task, even more so when its kinematics and its pose are not known precisely. In this paper, we present a visual motion capture system to allow both real-time measurements of robot joint angles and model estimation of its kinematics.
Unlike other humanoid robots, Ecce (see Fig. 1A) is completely molded by hand and its joints are not equipped with angle sensors. This anthropomimetic robot design [5] demands for both (i) real-time measurement of joint angles and (ii) model estimation of its kinematics. The underlying principle of this work is that all kinematic model parameters can be derived from visual motion data. Joint angle data finally lay the foundation for physics-based simulation and control of this novel musculoskeletal robot.
Recommended for submission to YRF2011 by supervisor Alois Knoll.
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References
Cheah, C., Liu, C., Slotine, J.: Adaptive tracking control for robots with unknown kinematic and dynamic properties. Intl. J. of Robotics Research 25(3), 283 (2006)
Fischler, M., Bolles, R.: Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24(6), 381–395 (1981)
Gamage, S., Lasenby, J.: New least squares solutions for estimating the average centre of rotation and the axis of rotation. J. of Biomechanics 35(1), 87 (2002)
Gaschler, A.: Real-Time Marker-Based Motion Tracking: Application to Kinematic Model Estimation of a Humanoid Robot. Master’s thesis, Technische Universität München, Germany (2011)
Jäntsch, M., Wittmeier, S., Knoll, A.: Distributed Control for an Anthropomimetic Robot. In: Intl. Conf. on Intelligent Robots and Systems, pp. 5466–5471 (2010)
Marques, H., Jäntsch, M., Wittmeier, S., Holland, O., Alessandro, C., Diamond, A., Lungarella, M., Knight, R.: Ecce1: The first of a series of anthropomimetic musculoskeletal upper torsos. In: Humanoid Robots, pp. 391–396 (2010)
Pintaric, T., Kaufmann, H.: Affordable infrared-optical pose-tracking for virtual and augmented reality. In: Proc of Trends and Issues in Tracking for Virtual Environments Workshop, pp. 44–51 (2007)
Steinicke, F., Jansen, C., Hinrichs, K., Vahrenhold, J., Schwald, B.: Generating Optimized Marker-based Rigid Bodies for Optical Tracking Systems. In: Intl. Conf. on Computer Vision Theory and Applications (2007)
Trucco, E., Fusiello, A., Roberto, V.: Robust motion and correspondence of noisy 3-D point sets with missing data. Pattern recognition letters 20(9), 889–898 (1999)
Umeyama, S.: Least-squares estimation of transformation parameters between two point patterns. Pattern Analysis and Machine Intelligence, 376–380 (1991)
Urata, J., Nakanishi, Y., Miyadera, A., Mizuuchi, I., Yoshikai, T., Inaba, M.: A three-dimensional angle sensor for a spherical joint using a micro camera. In: Proc. Intl. Conf. on Robotics and Automation, pp. 4428–4430 (2006)
Wang, X., Cheng, Y.Q., Collins, R.T., Hanson, A.R.: Determining correspondences and rigid motion of 3-d point sets with missing data. In: Computer Vision and Pattern Recognition, pp. 252–257 (1996)
Wittmeier, S., Gaschler, A., Jäntsch, M., Dalamagkidis, K., Knoll, A.: Calibration of a physics-based model of an anthropomimetic robot using evolution strategies. In: Intl. Conf. on Intelligent Robots and Systems (submitted, 2011)
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Gaschler, A. (2011). Visual Motion Capturing for Kinematic Model Estimation of a Humanoid Robot. In: Mester, R., Felsberg, M. (eds) Pattern Recognition. DAGM 2011. Lecture Notes in Computer Science, vol 6835. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23123-0_45
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DOI: https://doi.org/10.1007/978-3-642-23123-0_45
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