Aiming at application requirements of our spherical amphibious robot, which has one type of propulsion system to be used both on land and in water, an improved tracking learning detection (TLD) algorithm is designed and implemented, so as to improve the robustness and environmental adaptability of its visual detection system. First, binary normalized gradient method is implemented to reduce the number of image candidate samples. Second, the compressive sensing algorithm is introduced to speed

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... the image feature calculation. Then, some common videos are applied to test the performance of the improved TLD algorithm, and the results show that the average frame rate of the improved TLD algorithm is increased. Finally, to evaluate the feasibility and effectiveness of the improved TLD algorithm in the visual system of our amphibious spherical robot, a series of experiments are carried out with illumination changes and in underwater environment. Comparison experimental results demonstrated that the improved TLD algorithm has better effectiveness, robustness and real-time performance than the traditional TLD algorithm.