Robotic Locomotion and Control

Context-dependent coordination of movement in Tribolium castaneum larvae

This study analyzes the locomotion of Tribolium castaneum larvae, revealing a context-dependent gait and the role of pygopods in movement across different substrates.

Balancing central control and sensory feedback produces adaptable and robust locomotor patterns in a spiking, neuromechanical model of the salamander spinal cord

This paper develops a spiking neuromechanical model of the salamander spinal cord to show that intermediate proprioceptive feedback improves locomotion coordination and robustness.

I2Bot: an open-source tool for multi-modal and embodied simulation of insect navigation

I2Bot simulates insect navigation by integrating morphology, sensory capabilities, and environment, revealing navigation principles for robotics.

Damage explains function in spiking neural networks representing central pattern generator

The paper develops a spiking neural network model of the central pattern generator to study distributed computations and shows that lesioning different neural elements affects CPG function differently.

Operation regimes of spinal circuits controlling locomotion and role of supraspinal drives and sensory feedback

This study develops a computational model of spinal locomotor circuits in cats to show that the spinal network operates in different regimes depending on locomotor speed and supraspinal input.

Sensory Feedback and Central Neuronal Interactions in Mouse Locomotion

This study develops a mathematical model of mouse locomotion to investigate the roles of sensory feedback and central interactions in gait control.

Sensorimotor delays constrain robust locomotion in a 3D kinematic model of fly walking

This study uses a 3D kinematic model of fly walking to show that sensorimotor delays limit robust locomotion, with performance degrading when delays exceed physiological ranges.

New Neural Controller Generalises Modular Control Across Lower-Limb Tasks Using Internal Models

This paper introduces a modular neural controller that transitions between lower-limb motor tasks using internal models and functional muscle synergies in a simulation.

Investigating the roles of reflexes and central pattern generators in the control and modulation of human locomotion using a physiologically plausible neuromechanical model

This paper presents a physiologically plausible neuromechanical model to study spinal control of human locomotion, showing that CPGs are necessary for rhythmic movement and that reflexes primarily provide inhibitory feedback.

A hierarchical model for external electrical control of an insect, accounting for inter-individual variation of muscle force properties

The paper develops a hierarchical model to control insect movement via electrical stimulation, showing that stimulus-torque relationships are linear but vary between individuals.

The BCM rule allows a spinal cord model to learn rhythmic movements

The paper demonstrates that a spinal cord model can learn rhythmic movements using the BCM learning rule, without requiring rhythm generating neurons or genetically defined connectivity.

neuroWalknet, a controller for hexapod walking allowing for context dependent behavior

The paper introduces neuroWalknet, a decentralized controller for hexapod walking that exhibits context-dependent behaviors and explains biological reflexes through emergent properties.

High-level motor planning allows flexible walking at different gait patterns in a neuromechanical model

The paper presents a neuromechanical model that demonstrates flexible walking at different gait patterns by using high-level motor planning and fixed low-level reflex loops.

A Neuromuscular Model of Human Locomotion Combines Spinal Reflex Circuits with Voluntary Movements

This paper presents a neuromuscular model of human locomotion that integrates spinal reflex circuits with voluntary movements to generate stable, rhythmic walking patterns with real-time adaptability.

NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster

NeuroMechFly is a neuromechanical model of Drosophila melanogaster that simulates biomechanics and neural control to predict behaviors and optimize locomotion.

Network architecture producing swing to stance transitions in an insect walking system

The paper constructs a neural network model of the stick insect's walking system to explain phase transitions in motor activity observed in isolated ganglia.

Forward simulations of walking on a variable surface-impedance treadmill: A comparison of two methods

This study compares two simulation methods to model human gait adaptation to asymmetrical surface stiffness, revealing biomechanical changes and the impact of damping on muscle activity.

Achieving natural behavior in a robot using neurally inspired hierarchical control

This paper presents a quadrupedal robot that achieves natural locomotion through a neurally inspired hierarchical control system without training or internal models.

An optimality principle for locomotor central pattern generators

The paper proposes an optimality principle for combining central pattern generators and reflex circuits in locomotion, showing how uncertainty-driven feedback optimizes gait stability and energy efficiency.

Sensory modulation of gait characteristics in human locomotion: a neuromusculoskeletal modeling study

This study identifies key reflex parameters that modulate gait characteristics through neuromechanical simulations of human locomotion.

A neuromechanical model of multiple network rhythmic pattern generators for forward locomotion in C. elegans

The paper investigates whether multiple network rhythmic pattern generators in C. elegans can drive forward locomotion without pacemaker neurons or stretch-receptor feedback using a simulation model.

On the organization of the locomotor CPG: insights from split-belt locomotion and mathematical modeling

This paper investigates the organization of locomotor CPG circuits by testing a hypothesis about state-dependent changes in rhythm generator operation using experimental and mathematical modeling approaches.

Biological data questions the support of the self inhibition required for pattern generation in the half center model.

The paper questions the validity of self-inhibitory mechanisms in the half-center model of locomotion control using in vivo data and functional evaluations.

Dynamical determinants of different spine movements and gait speeds in rotary and transverse gallops

This study develops a model to analyze spine movements and gait speeds in rotary and transverse gallops, finding that flight type is determined by ground reaction force effects on spine movement direction and that rotary gallops achieve higher speeds due to longer flight duration.

Unraveling intra- and intersegmental neuronal connectivity between central pattern generating networks in a multi-legged locomotor system

The paper investigates neuronal connectivity between central pattern generating networks in stick insect legs using experimental and modeling approaches to identify coupling structures and strengths.

Kinematic and biomechanical analyses in Drosophila suggests that most legged locomotion in insects can be understood within a single framework.

This study analyzes Drosophila legged locomotion and finds that a tripod gait can explain both slow and fast kinematic patterns through a unified biomechanical model.

Intrinsic and Extrinsic Modulation of C. elegans Locomotion

The paper studies how neural, mechanical, and environmental factors modulate locomotion in C. elegans using a computational model.

Neuromechanical phase lag predicts material and neural control properties in Caenorhabditis elegans

The paper investigates how sensory inputs affect neuromechanical phase lag and locomotion speed in C. elegans by modeling feed forward and feedback controlled undulations.

Model of a bilateral Brown-type central pattern generator for symmetric and asymmetric locomotion

The paper provides an analytical solution to a Brown-type CPG model, demonstrating its efficiency and ability to control symmetric and asymmetric locomotion through parametric sensitivity analysis.