The interplay between robotics and neuromechanics facilitates discoveries in both fields: nature provides roboticists with design ideas, while robotics research elucidates critical features that confer performance advantages to biological systems. Here, we explore a system particularly well suited to exploit the synergies between biology and robotics: high-speed antenna-based wall following of the American cockroach (Periplaneta americana). Our approach integrates mathematical and hardware modeling with behavioral and neurophysiological experiments. Specifically, we corroborate a prediction from a previously reported wall-following template - the simplest model that captures a behavior - that a cockroach antenna-based controller requires the rate of approach to a wall in addition to distance, e.g., in the form of a proportional-derivative (PD) controller. Neurophysiological experiments reveal that important features of the wall-following controller emerge at the earliest stages of sensory processing, namely in the antennal nerve. Furthermore, we embed the template in a robotic platform outfitted with a bio-inspired antenna. Using this system, we successfully test specific PD gains (up to a scale) fitted to the cockroach behavioral data in a "real-world" setting, lending further credence to the surprisingly simple notion that a cockroach might implement a PD controller for wall following. Finally, we embed the template in a simulated lateral-leg-spring (LLS) model using the center of pressure as the control input. Importantly, the same PD gains fitted to cockroach behavior also stabilize wall following for the LLS model.

It may come as no surprise that a simple "planar unicycle" (or "skate") model can successfully follow a wall at high speed under PD-control. What would be surprising is that such a simple control mechanism may underly the control of one of nature's fastest terrestrial insects, the American cockroach. For this paper, we implemented the same controller (up to scale) believed to govern cockroach wall following to successfully control two models of the cockroach: a differential-drive mobile robot with a flexible artificial antenna and a lateral leg spring model with moving center of pressure as the control input. These physical and numerical experiments demonstrate the sufficiency of the cockroach's putative controller in a real-world setting with unmodeled effects, and suggest how the nervous system might guide leg placement in response to sensory stimuli. This hierarchy of models may prove useful in generating prescriptive hypotheses for biological testing and hence elucidating the general principles that underly sensor-guided animal locomotion.

Feedback from antennae - long, flexible tactile sensors - enables cockroaches and other arthropods to rapidly maneuver through poorly lit and cluttered environments. Inspired by their performance, we created a wall-following controller for a dynamic wheeled robot using tactile antenna feedback. We show this controller is stable for a wide range of control gains and robot system parameters. To test the controller, we constructed a two-link antenna that uses potentiometers and capacitive contact sensors. Experiments based on the prototype demonstrate that our controller robustly tracks unexpected corners ranging from -60° to +900.