Singularly Perturbed Averaging with Application to Bio-Inspired 3D Source Seeking

We propose a novel 3D source seeking algorithm for rigid bodies with a non-collocated sensor inspired by the chemotactic navigation strategy of sea urchin sperm known as helical klinotaxis. We work directly with the rotation group SO(3) without parameterization in representing the attitude of a rigid body. As a consequence, the proposed algorithm does not require attitude feedback for implementation as opposed to all previous work on 3D source seeking. The stability of the proposed algorithm is proven using an intricate combination of singular perturbation and second order averaging.