Motor control beyond reach—how humans hit a target with a whip

Abstract

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.

Finding the rhythm: Humans exploit nonlinear intrinsic dynamics of compliant systems in periodic interaction tasks

“…Multiple robotic experiments [20, 23, 24] have shown that moving a system along its modes is very energy efficient, as the system is supported in a motion it is intrinsically inclined to follow and therefore only little control effort is needed to sustain this motion. Inspired by these findings and the observations of Hogan and Sternad in various works that humans seek predictability and low sensorimotor effort in dynamic interactions [1, 2, 6–8], we hypothesize that humans intuitively choose a control strategy to drive a compliant system that matches the intrinsic system dynamics as these are easier to stabilize. To test this hypothesis, we need to compare the motion that the human excites in a system during a dynamic interaction with the intrinsic motion, i.e.…”

“…This implies that humans must be able to estimate the dynamics of external objects through haptic interactions. This idea is also supported by recent works from the research groups of Hogan and Sternad [1,2,[6][7][8].…”

“…This implies that humans must be able to estimate the dynamics of external objects through haptic interactions. This idea is also supported by recent works from the research groups of Hogan and Sternad [1, 2, 6–8]. One of their studies showed that humans simplified constrained motion tasks by taking advantage of interactive dynamics and tuning their hand impedance to the system rather than applying precise force control [6].…”

“…Multiple robotic experiments [20,23,24] have shown that moving a system along its modes is very energy efficient, as the system is supported in a motion it is intrinsically inclined to follow and therefore only little control effort is needed to sustain this motion. Inspired by these findings and the observations of Hogan and Sternad in various works that humans seek predictability and low sensorimotor effort in dynamic interactions [1,2,[6][7][8], we The lower link angle q 2 is defined relative to the upper link. d) Schematic illustration of the linear mode for a 1-DOF system, i.e., the simple pendulum with coordinates q 1 .…”

“…Further, a cup balancing task experiment showed that participants always chose similar starting positions to initialize the task [7], indicating that the participants could get an intuitive feeling of the system dynamics. Even in experiments with a system with very complex dynamics, such as a whip, humans might excite the simple intrinsic modes of the system to hit a target [8]. Thus, for interactions with dynamic systems, experiments support the idea that humans can effectively estimate and make use of the system dynamics.…”