Human dexterity far exceeds that of modern robots, despite a much slower neuromuscular system. Understanding how this is accomplished may lead to improved robot control. The slow neuromuscular system of humans implies that prediction based on some form of internal model plays a prominent role. However, the nature of the model itself remains unclear. To address this problem, we focused on one of the most complex and exotic tools humans can manipulate-a whip. We tested (in simulation) whether a distant target could be reached with a whip using a (small) number of dynamic primitives, whose parameters could be learned through optimization. This approach was able to manage the complexity of an (extremely) high degree-of-freedom system and discovered the optimal parameters of the upper-limb movement that achieved the task. A detailed model of the whip dynamics was not needed for this approach, which thereby significantly relieved the computational burden of task representation and performance optimization. These results support our hypothesis that composing control using dynamic motor primitives may be a strategy which humans use to enable their remarkable dexterity. A similar approach may contribute to improved robot control.

Humans are strikingly adept at manipulating complex objects, from tying shoelaces to cracking a bullwhip. These motor skills have highly nonlinear interactive dynamics that defy reduction into parts. Yet, despite advances in data recording and processing, experiments in motor neuroscience still prioritize experimental reduction over realistic complexity. This study embraced the fully unconstrained behaviour of hitting a target with a 1.6-m bullwhip, both in rhythmic and discrete fashion. Adopting an object-centered approach to test the hypothesis that skilled movement simplifies the whip dynamics, the whip's evolution was characterized in relation to performance error and hand speed. Despite widely differing individual strategies, both discrete and rhythmic styles featured a cascade-like unfolding of the whip. Whip extension and orientation at peak hand speed predicted performance error, at least in the rhythmic style, suggesting that humans accomplished the task by setting initial conditions. These insights may inform further studies on human and robot control of complex objects.

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Manipulation of flexible objects is one of the major challenges in robotics as the nonlinear dynamics of the high-dimensional object structure makes it difficult to apply current control methods. A previous simulation study showed that control with few pre-structured joint trajectories coupled with joint impedance (dynamic primitives) could control a 25-dimensional whip to hit a target. This was possible even though the impedance values were constant. This paper explores whether time-varying impedance throughout the movement may further enhance performance. We present an online impedance adaptation (OIA) controller that modulates the joint impedances of a two-joint actuator in real time for the same task. Results showed that the OIA control method increased the speed of optimization and resulted in smaller deviation from the zero-torque joint trajectories compared to the controller with constant joint impedances. This novel way to modulate both motion and impedance of a manipulator may facilitate the control of flexible objects with significant dynamics.

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The formation and development fragment of history of human-machine interaction in the operator – central observation panel system of the Non-departmental Security Service of the Federal National Guard Troops Service in terms of technological progress relationship with the formation of human experience and the world picture based on it is considered in the article.