Integration of intrinsic muscle properties, feed-forward and feedback signals for generating and stabilizing hopping

Abstract

It was hypothesized that a tight integration of feed-forward and feedback-driven muscle activation with the characteristic intrinsic muscle properties is a key feature of locomotion in challenging environments. In this simulation study it was investigated whether a combination of feed-forward and feedback signals improves hopping stability compared with those simulations with one individual type of activation. In a reduced one-dimensional hopping model with a Hill-type muscle (one contractile element, neither serial nor parallel elastic elements), the level of detail of the muscle's force -length -velocity relation and the type of activation generation (feed-forward, feedback and combination of both) were varied to test their influence on periodic hopping. The stability of the hopping patterns was evaluated by return map analysis. It was found that the combination of feed-forward and proprioceptive feedback improved hopping stability. Furthermore, the nonlinear Hill-type representation of intrinsic muscle properties led to a faster reduction of perturbations than a linear approximation, independent of the type of activation. The results emphasize the ability of organisms to exploit the stabilizing properties of intrinsic muscle characteristics.

Preparing the leg for ground contact in running: the contribution of feed-forward and visual feedback

“…This could be the reason for the modulated feed-forward pattern, which allows adapted pre-activation and thus adapted leg properties at touchdown without any proprioceptive feedback. Simple models, which explicitly consider muscle dynamics, confirmed that either an identical configuration at touchdown, in combination with proprioceptive feedback during ground contact (Geyer et al, 2003;Haeufle et al, 2012), or a feedforward strategy varying with flight time (Haeufle et al, 2010) allows the stabilization of periodic movements.…”

Evaluating Morphological Computation in Muscle and DC-Motor Driven Models of Hopping Movements

“…More precisely, the higher MC in the MusFib model can be attributed to the force-velocity characteristics of the muscle fibers. Previous hopping simulations showed that these non-linear contraction dynamics reduce the influence of the controller on the actual hopping kinematics (Haeufle et al, 2010(Haeufle et al, , 2012. This means, that the kinematic trajectory is more predetermined by the material properties as compared to the linearized muscle model MusLin, or the motor model DCMot.…”

“…Muscles also reduce the influence of the controller on the actual kinematics (they can act as a low-pass filter). This means that the hopping kinematics of the system is more predetermined with non-linear muscle characteristics than with simplified linear muscle characteristics (Haeufle et al, 2012). And finally, in hopping movements, muscles reduce the control effort (amount of information required to control the movement) by a factor of approximately 20 in comparison to a DC-motor driven movement (Haeufle et al, 2014).…”

“…Several simulation studies have shown that the muscles' typical non-linear contraction dynamics can be exploited in movement generation with very simple control strategies (Schmitt and Haeufle, 2015). Muscles improve movement stability in comparison to torque driven models (van Soest and Bobbert, 1993) or simplified linearized muscle models [for an overview see (Haeufle et al, 2012)]. Muscles also reduce the influence of the controller on the actual kinematics (they can act as a low-pass filter).…”

“…In the MusFib model, the leg force is modeled to incorporate the active muscle fibers' contraction dynamics. The model has been motivated and described in detail elsewhere (Haeufle et al, 2010(Haeufle et al, , 2012(Haeufle et al, , 2014. In a nutshell, the material properties of the muscle fibers are characterized by two terms modulating the leg force The first term q(t) represents the muscle activity.…”