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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. 

Walking is the most common form of how animals move on land. The model organismDrosophila melanogasterhas become increasingly popular for studying how the nervous system controls behavior in general and walking in particular. Despite recent advances in tracking and modeling leg movements of walkingDrosophilain 3D, there are still gaps in knowledge about the biomechanics of leg joints due to the tiny size of fruit flies. For instance, the natural alignment of joint rotational axes was largely neglected in previous kinematic analyses. In this study, we therefore present a detailed kinematic leg model in which not only the segment lengths but also the main rotational axes of the joints were derived from anatomical landmarks, namely, the joint condyles. Our model with natural oblique joint axes is able to adapt to the 3D leg postures of straight and forward walking fruit flies with high accuracy. When we compared our model to an orthogonalized version, we observed that our model showed a smaller error as well as differences in the used range of motion (ROM), highlighting the advantages of modeling natural rotational axes alignment for the study of joint kinematics. We further found that the kinematic profiles of front, middle, and hind legs differed in the number of required degrees of freedom as well as their contributions to stepping, time courses of joint angles, and ROM. Our findings provide deeper insights into the joint kinematics of walking inDrosophila, and, additionally, will help to develop dynamical, musculoskeletal, and neuromechanical simulations.