Coupling spiking neural networks and mechanical simulations to investigate walking and swimming in salamanders

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P7

Bio-inspired Controllers Facilitate Sim-to-Real Transfer

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P7

An integrated neuromechanical model of the mouse to study neural control of locomotion

The 11th International Symposium on Adaptive Motion of Animals and Machines. Kobe University, Japan. 2023-06-06/09. Adaptive Motion of Animals and Machines Organizing Committee.Poster Session P7

Multi-Objective Optimization based 3D Walking of a Neuromuscular Driven Salamander Model in Simulation

The 9.5th international symposium on Adaptive Motion of Animals and Machines. Ottawa，Canada (Virtual Platform). 2021-06-22/25. Adaptive Motion of Animals and Machines Organizing Committee

Fast multi-contact whole-body motion planning with limb dynamics

We present a new method for multi-contact motion planning which efficiently encodes internal dynamics of the robot without needing to use full models. Our approach is based on a five-mass model which is formulated by Cartesian points instead of joint angles. We solve direct optimization problems which include distance constraints between these points, Newtonian equations and integration constraints. We consider a given rhythm of contact switches but leave the phase-timings and contact positions free inside the optimization to provide more flexibility. Due to simpler equations and sparser problem structures, we can achieve very short optimization times in the order of few hundred milliseconds, which make the method suitable for application of online model predictive control. Aside from contact position and time adjustment properties, we can include precise foothold regions and synthesize dynamic motions by taking internal dynamics and momentums into account

Recapitulation of Drosophila Antennal Grooming by Combining Discrete and Rhythmic Movement Primitives

The 9.5th international symposium on Adaptive Motion of Animals and Machines. Ottawa，Canada (Virtual Platform). 2021-06-22/25. Adaptive Motion of Animals and Machines Organizing Committee

Coupling-dependent convergence behavior of phase oscillators with tegotae-control

A bio-inspired way to model locomotion is using a network of coupled phase oscillators to create a Central Pattern Generator (CPG). The recently developed feedback control method tegotae includes exteroceptive force feedback into the governing phase update equations, leading to gait limit cycles. However, the oscillator coupling weights are often determined empirically. Here, we first investigate how the coupling coeffi- cients influence the limit cycle convergence behavior on a 2- and 3-limbed structure in simulation. We find that the convergence with tegotae can be improved by introducing appropriate cross- couplings. This results in a smoother convergence and steady- state behavior where each individual oscillator drives the full network to a common convergence state in comparison to competing convergence states with ill-chosen cross-couplings. We then validate the findings in hardware and hypothesize how the appropriate couplings could be derived directly from the morphology, potentially eliminating the empiric determination.This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) RoboPatient grant [EP/T00603X/1]