Tunable muscular damping to increase morphological computation in legged locomotion

• Applicants: Professor Dr. Alexander Badri-Spröwitz; Professor Dr. Daniel Häufle; Professor Dr. Tobias Siebert
• Subject Area: Automation, Mechatronics, Control Systems, Intelligent Technical Systems, Robotics
• Term: since 2021
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 449912641

The animal's (including human's) neuromuscular control system seemingly effortless balances power generation, energy dissipation, and energy storage, for the complex task of robust and agile legged locomotion. For this, biological systems rely on the visco-elastic properties of muscle-tendon units to perform `morphological computation', i.e., a contribution of the physical structures to the control. Especially in unknown ground conditions, where the systems kinetic energy differs at every impact, the visco-elastic properties of the muscle-tendon units generate the first response to unknown ground conditions. With this, they achieve robust and agile locomotion despite neuronal delays which may be as large as 40% of the duration of a stance phase. This first visco-elastic response depends on the muscle activity, and, hence, on the neuronal control. Tuning this instantaneous response allows to create a prepared and adaptive behavior and is therefore crucial for animals. However, especially the contribution of tunable damping to this `morphological computation' has never been investigated systematically.It is therefore the main objective of this project to investigate, how biological legged systems may exploit tunable damping characteristics in dynamic locomotion. More specifically, the project investigates the following hypotheses: 1) Morphological computation can be increased by exploiting tunable damping. 2) Tunable damping allows increasing the working range of serial elastic actuators and, therefore, the agility in locomotion. 3) The trade-off between morphological computation, energy efficiency, robustness, and agility can be adjusted by tuning of damping in perturbed locomotion.To investigate these hypotheses, we propose to develop and combine three modelling approaches: a) A neuromuscular, biomechanical computer model incorporating new insights and hypotheses on muscular damping. b) An actuated and sensorized legged robot setup which includes muscle-inspired passive but tunable physical damping. c) A muscle model predicting realistic eccentric muscle fibre forces and energy efficiency in cyclic locomotion on the basis of experimentally determined viscoelastic fibre characteristics.As such, this interdisciplinary project bridges computer modelling, robotic hardware, and muscle physiology approaches to investigate the contribution of `morphological computation' to robust and agile bipedal locomotion. Especially the exploitation of muscular damping by low-level control in the sense of `morphological computation' will be quantified for the first time.

• DFG Programme: Research Grants