Wireless obstacle detection and characterization by multimodal helical nanoswimmers

Magnetically actuated micro/nano robots are promising to various biological and medical applications in wet environments. In order to improve robots control, robustness and efficiency, real time 3D topographical surface analysis are essential especially for their navigation under such wet and confined environments. In this paper we propose a swimmer from the Roll-To-Swim (RTS) family capable of detecting and characterizing its surrounding topography thanks to 2D optical feedback. This RTS detects the presence of an obstacle (6.5µm height) by detecting perturbations in its horizontal rolling motion. Then we reconstruct a 2D probabilistic map of obstacles presence. To further characterize the surface topography, we developed the spintop motion where the RTS stands vertically while rotating. We provide a speed characterization of this new motion and demonstrate its maneuverability by integrating it in a closed-loop path following control. In this motion, RTS can be trapped by a targeted obstacle. The amount of power needed to escape is used to characterize the height of the obstacle from 2.5 to 6.5µm with a precision of 2µm. This wireless topographical detection by RTS can be a promising tool to choose an efficient pathway and an appropriate motion adapted to the surrounding environment as well as a surface topography analyzer.