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Comparing with the local algorithm in stereo matching, the global algorithm can get highly quality disparity space image (DSI) usually. The graph cuts algorithm, as the traditional global matching method, can get the highly quality DSI with long computation time, so the graph cuts algorithm is difficult to used in real-time matching applications. In this paper, a new method is proposed to accelerate the matching speed. Firstly, the segments of the image are calculated using the Gaussians pyramid (DoGs) computing method, secondly calculate the disparity range of two corresponding image segments in image pair using the color feature, and every segment pair is matched based on graph cuts algorithm according to the offset of disparity range in parallel time, finally all the segments are assembled into a whole disparity image. The experimental results show that the matching speed is accelerated greatly with a high disparity image quality.

A new type of integration robot of arm and leg has been developed. Its cross gait of walking quickly on the barrier-free road was designed and planned. Gait optimization algorithm based on the energetic optimum was put forward, which can optimize the robot cross gait, and get the corresponding optimization parameters of walking gait. The simulation results show that the robot has the very good exercise continuity and stability on the basis of low energy consumption when it adopts the optimized cross gait.

A frog-inspired hopping leg is designed in this paper, and the pneumatic muscle is utilized as the driver. The muscles are bioarticular muscles which can not only increase the range of the joint angle, but also make the robot compliance more similar to real frogs. Kinematics analysis of pneumatic muscles is accomplished, and the experiments of motion simulations based on virtual components are given, as the theoretical basis of further design of the control system.