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Campaniform sensilla (CS) are mechanosensors embedded in the cuticle of insects. They are often found at locations near the joints of leg segments. On legs, CS are generally considered to respond directionally to cuticle bending during legged locomotion. It is currently unclear how CS locations affect strain levels at the CS, but this information is crucial for understanding how CS respond to stimuli. Here we present a parametric finite element model of the femoral CS field forDrosophilahind legs with 12 general and seven CS-specific parameters each. This model allows testing how changes in CS location, orientation and material property affect strain levels at each CS. We used experimentally acquired kinematic data and computed ground reaction forces to simulatein vivo-like forward stepping. The displacements found in this study at the physiological CS field location near the trochanter–femur joint are smaller than those necessary for conformation changes of ion channels involved in signal elicitation. Also, variation of material properties of the CS had little influence on displacement magnitudes at the CS cap where the sensory neuron attaches. Thus, our results indicate that ground reaction forces alone are unlikely to serve CS field activation during forward walking. 

Abstract For decades, the field of biologically inspired robotics has leveraged insights from animal locomotion to improve the walking ability of legged robots. Recently, “biomimetic” robots have been developed to model how specific animals walk. By prioritizing biological accuracy to the target organism rather than the application of general principles from biology, these robots can be used to develop detailed biological hypotheses for animal experiments, ultimately improving our understanding of the biological control of legs while improving technical solutions. In this work, we report the development and validation of the robot Drosophibot II, a meso-scale robotic model of an adult fruit fly, Drosophila melanogaster. This robot is novel for its close attention to the kinematics and dynamics of Drosophila, an increasingly important model of legged locomotion. Each leg’s proportions and degrees of freedom have been modeled after Drosophila 3D pose estimation data. We developed a program to automatically solve the inverse kinematics necessary for walking and solve the inverse dynamics necessary for mechatronic design. By applying this solver to a fly-scale body structure, we demonstrate that the robot’s dynamics fit those modeled for the fly. We validate the robot’s ability to walk forward and backward via open-loop straight line walking with biologically inspired foot trajectories. This robot will be used to test biologically inspired walking controllers informed by the morphology and dynamics of the insect nervous system, which will increase our understanding of how the nervous system controls legged locomotion. 

Sensory feedback from sense organs during animal locomotion can be heavily influenced by an organism’s mechanical structure. In insects, the interplay between sensing and mechanics can be demonstrated in the campaniform sensilla (CS) strain sensors located across the exoskeleton. Leg CS are highly sensitive to the loading state of the limb. In walking, loading is primarily influenced by ground reaction forces (GRF) mediated by the foot, or tarsus. The complex morphology of the tarsus provides compliance, passive and active substrate grip, and an increased moment arm for the GRF, all of which impact leg loading and the resulting CS discharge. To increase the biomimicry of robots we use to study strain feedback during insect walking, we have developed a series of tarsi for our robotic model of a Carausius morosus middle leg. We seek the simplest design that mimics tarsus functionality. Tarsi were designed with varying degrees of compliance, passive grip, and biomimetic structure. We created elastic silicone tarsal joints for several of these models and found that they produced linear stiffness within joint limits across different joint morphologies. Strain gauges positioned in CS locations on the trochanterofemur and tibia recorded strain while the leg stepped on a treadmill. Most, but not all, designs increased axial strain magnitude compared to previous data with no tarsus. Every tarsus design produced positive transversal strain in the tibia, indicating axial torsion in addition to bending. Sudden increases in tibial strain reflected leg slipping during stance. This data show how different aspects of the tarsus may mediate leg loading, allowing us to improve the mechanical biomimicry of future robotic test platforms.