Cockroach shelter-seeking strategy may look like an undirected random search, but we show that they are attracted to darkened shelters, arriving at a shelter in about half the time it would otherwise take. We were able to identify four statistically significant trends from the behavior of 134 cockroaches in one-minute naïve walking trials with four different arena configurations. By combining these trends into a model, we arrive at an algorithm that significantly directs a simulated agent to a location. This algorithm was then adapted and tested on a small mobile robot equipped with an onboard camera and antenna-like contact sensors.

Biological inspiration has long been pursued as a key to more efficient, agile and elegant control in robotics. It has been a successful strategy in the design and control of robots with both biologically abstracted and biomimetic designs. Behavioral studies have resulted in a good understanding of the mechanics of certain animals. However, without a better understanding of their nervous systems, the biologically-inspired observation-based approach was limited. The findings of Hess and Büschges, and Ekeberg et al. describing the neural mechanisms of stick insect intra-leg joint coordination have made it possible to control models of insect legs with a network of neural pathways they found in the animal's thoracic ganglia. Our work with this model, further informed by cockroach neurobiological studies performed in the Ritzmann lab, has led to LegConNet (Leg Controller Network). In this paper we show that LegConNet controls the forward stepping motion of a robotic leg. With hypothesized additional pathways, some later confirmed by neurobiology, it can smoothly transition the leg from forward stepping to turning movements. We hypothesize that commands descending from a higher center in the nervous system inhibit or excite appropriate local neural pathways and change thresholds, which, in turn, create a cascade of reflexes resulting in behavioral transitions.