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Impedance control is a compliance control strategy capable of accommodating both unconstrained and constrained motions. The performance of impedance controllers depends heavily upon environment dynamics and the choice of target impedance. To maintain performance for a wide range of environments, target impedance needs to be adjusted adaptively. In this paper, a geometric view on impedance control is developed for stiff environments, resulting in a “static-optimized ” controller that minimizes a combined generalized position and force trajectory error metric. To incorporate the dynamic nature of the manipulator-environment system, a new cost function is considered. A classic quadratic optimal control strategy is employed to design a novel adaptive compliance controller with control parameters adjusted based upon environment stiffness and damping. In steady state, the proposed controller ultimately implements the static-optimized impedance controller. Simulation and experimental results indicate that the proposed optimal controller offers smoother transient response and a better trade-off between position and force regulation. KEY WORDS—robot compliance control, robot impedance control, quadratic optimal control 1

Shared-Control Paradigms in Multi-operator-single-robot Teleoperation

Extending classical bilateral teleoperation systems to multi-user scenarios allows to broaden their capabilities and extend their applicability to more complex manipulation tasks. In this paper a classical Single-Operator-Single-Robot (SOSR) system is extended to a Multi-Operator-Single-Robot (MOSR) architecture. Two shared-control paradigms which enable visual only or visual and haptic coupling of the two human operators are introduced. A pointing task experiment was conducted to evaluate the two control paradigms and to compare them to a classical SOSR system. Results reveal that operators benefit from the collaborative task execution only if haptic interaction between them is enabled