A bio-inspired sighted robot chases like a hoverfly.

Here we present a novel bio-inspired visual processing system, which enables a robot to locate and follow a target, using an artificial compound eye called CurvACE. This visual sensor actively scanned the environment at an imposed frequency (50 Hz) with an angular scanning amplitude of [Formula: see text] and succeeded in locating a textured cylindrical target with hyperacuity, i.e. much finer resolution than the coarse inter-receptor angle of the compound eye. Equipped with this small, lightweight visual scanning sensor, a Mecanum-wheeled mobile robot named ACEbot was able to follow a target at a constant distance by localizing the right and left edges of the target. The localization of the target's contrasted edges is based on a bio-inspired summation of Gaussian receptive fields in the visual system. By means of its auto-adaptive pixels, ACEbot consistently achieved similar pursuit performances under various lighting conditions with a high level of repeatability. The robotic pursuit pattern mimics finely the behavior of the male fly Syritta Pipens L. while pursuing the female. The high similarity in the trajectories as well as the biomimicry of the visual system provides strong support for the hypothesis that flies do maintain center the target and constant its subtended angle during smooth pursuit. Moreover, we discuss the fact that such simple strategy can also provide a trajectory compatible with motion camouflage.

Stabilization of a (3,0) mobile robot by means of an event-triggered control.

Event-triggered control (ETC) is a sampling strategy that updates the control value only when some events related to the state of the system occurs. It therefore relaxes the periodicity of control updates without deteriorating the closed-loop performance. This paper develops a nonlinear ETC for the stabilization of a (3,0) mobile robot. The construction of an event function and a feedback function is carried out based on the existence of a stabilizing control law and a Control Lyapunov Function (CLF). The event function is dependent on the time derivative of the CLF and the feedback function results from the extension of Sontag's formula, which ensures asymptotic stability, smoothness everywhere and continuity at the equilibrium. Experimental results, compared with a computed torque control, validate the theoretical analysis.