Since safe human-robot interaction is naturally linked to compliance in these robots, this requirement presents a challenge for the positioning accuracy. The class of variablestiffness robots features intrinsically soft contact behavior where the physical stiffness can even be altered during operation.Here we present a control scheme for bidirectional, antagonistic variable-stiffness actuators that achieve high-precision link-side trajectory tracking while simultaneously ensuring compliance during physical contact. Furthermore, the approach enables to regulate the pretension in the antagonism. The theoretical claims are confirmed by formal analyses of passivity during physical interaction and the proof of uniform asymptotic stability of the desired link-side trajectories. Experiments on the forearm joint of the DLR robot David verify the proposed approach.
We propose an impedance controller for articulated soft robots implemented by bidirectional antagonistic variable stiffness (BAVS) actuation, where two motors are connected via nonlinear elastic elements to a single link allowing for a joint stiffness modulation. Naturally, the highly elastic elements introduce undesired oscillatory dynamics into the plant. To address this problem, we present a controller that allows to impose a desired link-side stiffness and damping behavior while preserving the intrinsic inertial elastic properties of the system. This allows us to solve the global asymptotic regulation problem while simultaneously imposing a desired joint stiffness preset on the BAVS actuator. We provide a passivity and stability analysis based on a physically motivated storage and Lyapunov function. Experimental results on the underarm BAVS joint of DLR David validate our control law.
In the modern manufacturing process, novel technologies enable the collaboration between humans and robots, which increases productivity while keeping flexibility. However, these technologies also lead to new challenges, e.g., maximization of Human-Robot Collaboration (HRC) performance while ensuring safety for the human being in fenceless robot applications. In this paper, an approach of the dynamic human motion projection is proposed for typical assembly tasks. The human upper body is simplified as a five-degree-of-freedom (5-DOF) rigid-body model. A control-oriented projection model is proposed, and its parameters are estimated from the test data of human capability. Combined with a human-state estimator and a collision estimator, the "worst-case" collision motion is projected in the HRC scenario. The dynamic projection method is feasible online. Finally, the estimated collision time is adopted to increase the robot's speed limit, which validates the improvement of HRC's efficiency.
In the past, several motion and force controls were successfully implemented on rigid-joint robots with constraints. With the invention of mechanically compliant robots, the focus on designing controllers for elastic joint robots with constraints is increasing, especially involving the complexity of the joint elasticity in control. Aiming to bridge the gap between the control schemes of rigid-and elastic-joint robots, this letter presents a controller consisting of a PD+ task-space tracking and integral force control, while the intrinsic inertial and elastic properties of the system are fully preserved. We provide a passivity analysis and prove uniform asymptotic stability of the equilibrium. Simulations on a planar two-armed benchmark system with constraints validate the proposed control law.
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