Abstract
Since human motion is not completely repeatable, the synthesis of robot trajectories for human–robot cooperation must allow for easy modulation. This should take place by taking into account the external sensory feedback that enables interpretation of the person’s intentions. In this chapter we present a method for coupling of robot trajectories to the measured force feedback arising from the interaction with the environment, where the environment can be an object, a robot, or a person. The algorithm is based on Dynamic Movement Primitives, a kinematic representation of robot trajectories. In the chapter we show how to consider the measured external forces and torques within the kinematic DMP framework. We further develop the approach by introducing iterative learning control in order to anticipate the behavior and achieve minimal errors of motion for stationary conditions. The usefulness of the proposed approach was demonstrated on two KUKA LWR robots performing a bimanual human–robot collaborative task.
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Gams, A., Nemec, B., Petrič, T., Ude, A. (2014). Coupling of Trajectories for Human–Robot Cooperative Tasks. In: Lenarčič, J., Khatib, O. (eds) Advances in Robot Kinematics. Springer, Cham. https://doi.org/10.1007/978-3-319-06698-1_55
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DOI: https://doi.org/10.1007/978-3-319-06698-1_55
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