Soft robotics for the hydraulic atlas arms: Joint impedance control with collision detection and disturbance compensation. Vorndamme, J., Schappler, M., Tödtheide, A., & Haddadin, S. In 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 3360–3367, October, 2016. doi abstract bibtex Soft robotics methods such as impedance control and reflexive collision handling have proven to be a valuable tool to robots acting in partially unknown and potentially unstructured environments. Mainly, the schemes were developed with focus on classical electromechanically driven, torque controlled robots. There, joint friction, mostly coming from high gearing, is typically decoupled from link-side control via suitable rigid or elastic joint torque feedback. Extending and applying these algorithms to stiff hydraulically actuated robots poses problems regarding the strong influence of friction on joint torque estimation from pressure sensing, i.e. link-side friction is typically significantly higher than in electromechanical soft robots. In order to improve the performance of such systems, we apply state-of-the-art fault detection and estimation methods together with observer-based disturbance compensation control to the humanoid robot Atlas. With this it is possible to achieve higher tracking accuracy despite facing significant modeling errors. Compliant end-effector behavior can also be ensured by including an additional force/torque sensor into the generalized momentum-based disturbance observer algorithm from [1].
@inproceedings{vorndamme_soft_2016,
title = {Soft robotics for the hydraulic atlas arms: {Joint} impedance control with collision detection and disturbance compensation},
shorttitle = {Soft robotics for the hydraulic atlas arms},
doi = {10.1109/IROS.2016.7759517},
abstract = {Soft robotics methods such as impedance control and reflexive collision handling have proven to be a valuable tool to robots acting in partially unknown and potentially unstructured environments. Mainly, the schemes were developed with focus on classical electromechanically driven, torque controlled robots. There, joint friction, mostly coming from high gearing, is typically decoupled from link-side control via suitable rigid or elastic joint torque feedback. Extending and applying these algorithms to stiff hydraulically actuated robots poses problems regarding the strong influence of friction on joint torque estimation from pressure sensing, i.e. link-side friction is typically significantly higher than in electromechanical soft robots. In order to improve the performance of such systems, we apply state-of-the-art fault detection and estimation methods together with observer-based disturbance compensation control to the humanoid robot Atlas. With this it is possible to achieve higher tracking accuracy despite facing significant modeling errors. Compliant end-effector behavior can also be ensured by including an additional force/torque sensor into the generalized momentum-based disturbance observer algorithm from [1].},
booktitle = {2016 {IEEE}/{RSJ} {International} {Conference} on {Intelligent} {Robots} and {Systems} ({IROS})},
author = {Vorndamme, J. and Schappler, M. and Tödtheide, A. and Haddadin, S.},
month = oct,
year = {2016},
keywords = {Atlas humanoid robot, Collision avoidance, Friction, Impedance, Observers, Robot sensing systems, Torque, collision avoidance, collision detection, compliant end-effector behavior, elastic joint torque feedback, end effectors, fault detection-and-estimation method, feedback, force sensor, force sensors, friction, humanoid robots, hydraulic Atlas arms, hydraulic actuators, joint friction, joint impedance control, link-side control, link-side friction, momentum-based disturbance observer algorithm, observer-based disturbance compensation control, observers, partially-unknown potentially-unstructured environments, pressure sensing, reflexive collision handling, rigid feedback, soft robotics, stiff hydraulically actuated robots, torque control, torque measurement, torque sensor},
pages = {3360--3367}
}
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