CRCNS Research Project: Collaborative Research: Experimental, Numerical, and Robotic Study of the Role of Dynamic Load Sensing in Legged Locomotion

Insects are highly mobile walkers who adapt their muscle output to their ever‐changing environment. Force sensors in their legs detect increasing and decreasing forces, which may help them coordinate their legs and compensate for external forces, for example, when walking on an uneven surface. This Collaborative Research in Computational Neuroscience (CRCNS) project investigates the dynamics of the sensors that enable them to detect force increases and decreases, measuring the differences or similarities in these dynamics across the body, and exploring how these dynamics affect the control of walking.

Recordings from stick insect and cockroach legs will inform a neurorobotic model of insect locomotion. The model is a six‐legged robot with force sensors like those in insects. The robot's control system is based on the insect nervous system, enabling the investigators to test how dynamic force sensing affects muscle control.

Learning how to integrate dynamic force sensing into the robot's control system may lead to more successful walking robots for agriculture, mining, and exploration, and may shed light onto how humans utilize dynamic force sensing during locomotion. This project will also increase training in STEM through robotics workshops for West Virginia middle- and high-school students, and teaching and mentoring activities focused on women and first-generation college students.

To better understand the importance of sensing dynamic load (dF/dt) to the neural control of locomotion, the investigators will study the force sensing of stick insects and cockroaches, which are amenable to experimentation due to their external force sensing organs, campaniform sensilla (CS). Evidence suggests that CS support the synergistic activation of muscles throughout the leg, enhancing them to overcome postural perturbations and regulating them to limit muscle forces.

To better understand the organization of such synergies, the investigators will construct a neuromechanical model of the insect leg, whose kinematics and dynamics will provide necessary context for their afferent and efferent recordings. The investigators hypothesize that CS throughout the leg are tuned to rapidly recruit muscle synergies when the stance phase begins, to adapt motor outputs to variations in load during stance, and to support interleg coordination by signaling decreasing forces as the stance phase ends.

To immerse the CS model into the mechanical context of a walking body and perform experiments that would be impossible in vivo, the investigators will apply the model to their dynamically‐scaled neuro‐robotic model of an insect, Drosophibot, and record from strain sensors on all legs as it walks. Actuator torques and CS responses will be compared between the robot and animal to refine the investigators' models of dynamic force sensing and synergistic muscle recruitment.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.