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Load sensing is critical for walking behavior in animals, who have evolved a number of sensory organs and neural systems to improve their agility. In particular, insects measure load on their legs using campaniform sensilla (CS), sensory neurons in the cuticle of high-stress portions of the leg. Extracellular recordings from these sensors in a behaving animal are difficult to collect due to interference from muscle potentials, and some CS groups are largely inaccessible due to their placement on the leg. To better understand what loads the insect leg experiences and what sensory feedback the nervous system may receive during walking, we constructed a dynamically-scaled robotic model of the leg of the stick insect Carausius morosus. We affixed strain gauges in the same positions and orientations as the major CS groups on the leg, i.e., 3, 4, 6A, and 6B. The robotic leg was mounted to a vertically-sliding linear guide and stepped on a treadmill to simulate walking. Data from the strain gauges was run through a dynamic model of CS discharge developed in a previous study. Our experiments reveal stereotypical loading patterns experienced by the leg, even as its weight and joint stiffness is altered. Furthermore, our simulated CS strongly signal the beginning and end of stance phase, two key events in the coordination of walking. 

It is unknown precisely how the nervous system of invertebrates combines multiple sensory inputs to calculate more abstract quantities, e.g., combining the angle of multiple leg joints to calculate the position of the foot relative to the body. In this paper, we suggest that non-spiking interneurons (NSIs) in the nervous system could calculate such quantities and construct a neuromechanical model to support the claim. Range fractionated sensory inputs are modeled as multiple integrate-and-fire neurons. The NSI is modeled as a multi-compartment dendritic tree and one large somatic compartment. Each dendritic compartment receives synaptic input from one sensory neuron from the knee and one from the hip. Every dendritic compartment connects to the soma. The model is constructed within the Animatlab 2 software. The neural representation of the system accurately follows the true position of the foot. We also discuss motivation for future research, which includes modeling other hypothetical networks in the insect nervous system and integrating this model into task-level robot control.