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Title: Robust Underwater Obstacle Detection and Avoidance
Keywords: Obstacle Detection, Collision Avoidance, Occupancy Grids, Path Planning.
Issue Date: 7-Aug-2014
Source: VARADARAJAN GANESAN (2014-08-07). Robust Underwater Obstacle Detection and Avoidance. ScholarBank@NUS Repository.
Abstract: A robust obstacle detection and avoidance system is essential for long term autonomy of autonomous underwater vehicles (AUVs). Forward-looking sonars are usually used to detect and localize obstacles. However, such sensors have low signal-to-noise ratio (SNR) and a coarser resolution as compared to the electromagnetic sensors used in land and aerial based robots. Additionally, lack of GPS signals in underwater environments leads to poor localization of the AUV. This translates to uncertainty in the position of the obstacle relative to a global frame of reference. We propose an obstacle detection and avoidance algorithm for AUVs which is based on occupancy grids. First, we use a local occupancy grid that is attached to the body frame of the AUV, and not to the global frame in order to localize the obstacle accurately with respect to the AUV alone. Second, our technique adopts a probabilistic framework which makes use of probabilities of detection and false alarm to deal with the high amounts of noise present in the sonar data.This local probabilistic occupancy grid is used to extract potential obstacles which is then sent to the command and control (C2) system of the AUV. The C2 system checks for possible collision and executes an evasive maneuver accordingly. Experiments carried out at Pandan Reservoir in Singapore and at the sea in Selat Pauh of the coast of Singapore shows the viability of the proposed algorithm.
Appears in Collections:Master's Theses (Open)

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