Dung beetles show fascinating locomotion abilities. They can use their legs to not only walk but also manipulate objects. Furthermore, they can perform their leg movements at a proper frequency with respect to their biomechanical properties and quickly adapt the movements to deal with external perturbations. Understanding the principles of their biomechanics and neural computation and transferring them to artificial systems remain a grand challenge. According to this, we present here a first prototype of a real dung beetle-like leg developed by analyzing real dung beetle legs through micoCT scans. We also apply adaptive neural control, based on a central pattern generator (CPG) circuit with synaptic plasticity, to autonomously generate a proper stepping frequency of the leg. The controller can also adapt the leg movement to deal with external perturbations within a few steps.
Proceedings of the First International Symposium on Swarm Behavior and Bio-inspired Robotics, 2016