Stereo-vision based autonomous underwater navigation — The platform SARSTION

Underwater robotics has been the center of attention for a long time due to diverse multi-disciplinary applications that it addresses. Conventionally, the detection and navigation has been governed by the SONAR based systems. While, SONAR offers unmatched capability for long range operation, its performance is compromised for detection of short range objects. In this regard, an alternate solution based on image processing appears promising in short range applications. Stereo-vision based systems are now regularly deployed for surface applications with huge success. However, the underwater deployment of these stereo-vision based systems is still an open problem. In the current work, we present an underwater autonomous platform, navigated by stereo-vision based algorithm. Initially, we demonstrate the distinct edge that the stereo-vision enjoys over SONAR in terms of its low cost, small size and low energy requirements. We present a working prototype of a Semi-Autonomous Sub-Aquatic Robot for Surveillance using Stereo-vision (SARSTION). SARSTION provides 6 degrees of freedom, using propellers, 4 for horizontal motion and 2 for vertical motion and is administered by an elaborate control system based on various positional feedback sensors. The main contribution of the current work is in the design of a novel simplistic navigational algorithm. The two acquired images from a front looking stereo-camera are used to compute a depth map whose intensity represents the relative distance of an object from the camera. The intensities are then equated to compute the relative physical distances of different objects from the camera. This information coupled with the approximations of relative object sizes and the data from the positional feedback sensors are then used to carefully alter the yaw of the mechanical assembly to maneuver the robot. The camera can also be used to provide live feed, depending upon its usage. We present some promising results illustrating the successful operation of the robot in a controlled reservoir.