| Biological systems such as insects have often been used as a source of inspiration when developing legged robots. Insects are capable of nimbly navigating uneven terrain. This ability, combined with their observed behavioral complexity has made them a beacon for engineers, who have used behavioral data and hypothesized control systems to develop remarkably agile robots. Beyond pure inspiration, it is now becoming possible to directly implement models of relatively recent discoveries in insect nervous systems in hexapod robot controllers. Specifically, walking control based on a model of a network discovered in the stick insect's thoracic ganglia, and not just observed insect behavior, has now been implemented in a complete hexapod that is able to walk, perform a goal-seeking behavior, and obstacle surmounting behaviors such as single limb searching and elevator reflexes. Descending modulation of leg controllers is also incorporated via a "head module" that modifies leg controller parameters to accomplish turning in a role similar to the insect's higher centers. While many of these features have been previously demonstrated in simulation and with robotic subsystems, such as single- and two-legged test platforms, this is the first time that these neurobiological methods of control have been implemented in a complete, autonomous walking hexapod.;Many of these abilities have also been incorporated in previous hexapods by using more traditional engineering methods and methods based on external observations of insects. However, the methods described and used in this research, which are based on the actual neurobiological circuits found in the insect, are far simpler and therefore have much lower computational requirements. The reduced computation requirements lend themselves to small robots with limited on-board space available for the high-end processors needed for previous control methods.;This dissertation discusses the implementation of the biologically-grounded insect leg control method, descending modulation of that method, and the generation of stable, speed-dependent gaits. It then describes and quantifies the performance of the robot while navigating irregular terrain and performing phototaxis. Implementation is performed on the Biologically-Inspired Legged Locomotion - Ant - autonomous (BILL-Ant-a) hexapod robot. |
