Usability is one of the most important aspects of teleoperation. Ideally, the operator’s experience should be one of complete command over the remote environment, but also be as close as possible to what they would have if physically present at the remote end, i.e., transparency in terms of both action and perception. These two aspects may coincide in favorable conditions, where classic approaches such as the four-channel architecture ensures transparency of the control framework. In the presence of substantial delays between the user and the slave, however, the stability–performance trade-off inherent to bilateral teleoperation deteriorates not only transparency, but also command. An alternative, unilateral approach is given by tele-impedance, which controls the slave–environment interaction by measuring and remotely replicating the user’s limb endpoint position and impedance. Not including force feedback to the operator, tele-impedance is absolutely robust to delays, whereas it completely lacks transparency. This article introduces a novel control framework that integrates a new, fully transparent, two-channel bilateral architecture with the tele-impedance paradigm. The result is a unified solution that mitigates problems of classical approaches, and provides the user with additional tools to modulate the slave robot’s physical interaction behavior, resulting in a better operator experience in spite of time inconsistencies. The validity and effectiveness of the proposed solution is demonstrated in terms of performance in the interaction tasks, of user fatigue and overall experience.
In this work we propose a framework for bimanual teleoperation that includes two control strategies: (i) the classic one-to-one coupling of the human and robotic arms (which allows to fully exploit the user dexterity) and (ii) a new shared autonomy strategy, in which the two robotic arms are controlled through the movements and gestures of just one user's arm (relaxing the user's cognitive load). Moreover, the use of tele-impedance allows the user to also control the remote physical interaction.
With the aim of getting closer to the performance of the animal muscleskeletal system, elastic elements are purposefully introduced in the mechanical structure of soft robots. Indeed, previous works have extensively shown that elasticity can endow robots with the ability of performing tasks with increased efficiency, peak performances, and mechanical robustness. However, despite the many achievements, a general theory of efficient motions in soft robots is still lacking. Most of the literature focuses on specific examples, or imposes a prescribed behavior through dynamic cancellations, thus defeating the purpose of introducing elasticity in the first place.This paper aims at making a step towards establishing such a general framework. To this end, we leverage on the theory of oscillations in nonlinear dynamical systems, and we take inspiration from state of the art theories about how the human central nervous system manages the muscleskeletal system. We propose to generate regular and efficient motions in soft robots by stabilizing sub-manifolds of the state space on which the system would naturally evolve. We select these sub-manifolds as the nonlinear continuation of linear eigenspaces, called nonlinear normal modes. In such a way, efficient oscillatory behaviors can be excited. We show the effectiveness of the methods in simulations on an elastic inverted pendulum, and experimentally on a segmented elastic leg.
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