James R. Solberg, Ph.D. - US grants

Human telepresence underwater is essential for tasks such as security sweeps in harbors and oil field servicing. Co-robotic solutions are needed, because the risks are great for human divers, while autonomous robots do not deal well with contingencies. A major problem is that vision works poorly in murky environments, such as when mud is kicked up from the bottom. In this National Robotics Initiative (NRI) project the researchers are investigating and developing a replacement for vision -- electrosense -- used by Amazonian fish that navigate and hunt in murky water. These "weakly electric fish" generate an AC electric field that is perturbed by objects nearby. Electroreceptors covering the body of the fish detect the perturbations, which the fish decodes into information about its surroundings. The researchers are developing methods of preprocessing electric images for human understanding, and new computed methods for machine interpretation.

The research creates electrosense hardware and practical testbeds, for navigation and for manipulation underwater. It investigates methods and software to facilitate human interpretation of electric images, as well as machine interpretation. In hardware, the researchers are creating a kilopixel-scale electrosense array as an input sensor for human interpretation of electric images, and development of preprocessing algorithms to make human interpretation workable. The researchers are also using sparser and non-coplanar groups of electroreceptors on a manipulator, for control of pre-grasp and manipulation tasks. For human interpretation, electric image preprocessing includes contour painting and spatial high-pass filtering, as well as temporal filtering. For machine interpretation, methods include specific recognition strategies for simple geometric primitives, and sparse beamforming techniques for more complex environments.