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Vision-Based Deflection Estimation in an Anthropomorphic, Compliant and Lightweight Dual Arm

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ROBOT 2017: Third Iberian Robotics Conference (ROBOT 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 694))

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Abstract

This paper proposes the application of a stereo vision system for estimating and controlling the Cartesian and joint deflection in an anthropomorphic, compliant and ultra-lightweight dual arm designed for aerial manipulation. Each arm provides four degrees of freedom (DOF) for end-effector positioning in a human-like kinematic configuration. A simple and compact spring-lever mechanism introduced in all joints provides mechanical compliance to the arms. A color marker attached at the end effector of the arms is visually tracked by a stereo pair installed over the shoulders. The Cartesian position and velocity of the markers is estimated with an Extended Kalman Filter (EKF), while the corresponding points in an equivalent stiff-joint manipulator are obtained from the kinematic model and the position of the servos. The Cartesian deflection is defined as the difference between these two measurements, obtaining the joint deflection from the inverse kinematics. The vision-based deflection estimator is validated in test bench experiments: position estimation accuracy, impact response, passive/active compliance and contact force control.

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Acknowledgement

This work has been funded by the Spanish MINECO Retos project AEROMAIN (DPI2014-5983-C2-1-R) and by the H2020 AEROARMS Project, Grant Agreement Nº 644271. The research activity of Alejandro Suarez is supported by the Spanish Ministerio de Educacion, Cultura y Deporte FPU Program.

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Suarez, A., Heredia, G., Ollero, A. (2018). Vision-Based Deflection Estimation in an Anthropomorphic, Compliant and Lightweight Dual Arm. In: Ollero, A., Sanfeliu, A., Montano, L., Lau, N., Cardeira, C. (eds) ROBOT 2017: Third Iberian Robotics Conference. ROBOT 2017. Advances in Intelligent Systems and Computing, vol 694. Springer, Cham. https://doi.org/10.1007/978-3-319-70836-2_28

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  • DOI: https://doi.org/10.1007/978-3-319-70836-2_28

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-70836-2

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