Path planning and obstacle avoidance are essential for autonomous driving cars. On the base of a self-constructed smart obstacle avoidance car, which used a LeTMC-520 depth camera and Jetson controller, this paper established a map of an unknown indoor environment based on depth information via SLAM technology. The Dijkstra algorithm is used as the global path planning algorithm and the dynamic window approach (DWA) as its local path planning algorithm, which are applied to the smart car, enabling it to successfully avoid obstacles from the planned initial position and reach the designated position. The tests on the smart car prove that the system can complete the functions of environment map establishment, path planning and navigation, and obstacle avoidance.

In order to meet the performance requirements of global optimality and path smoothness in robot path planning, a new fusion algorithm of jump-A * algorithm and dynamic window approach is proposed. First, A * algorithm is optimized by using the jump point search method and a new distance evaluation function defined by Manhattan and Euclidean distance to obtain global path information. Then take the dynamic window approach as the core by integrating the global path information to safely plan a global optimal path with high smoothness. The experimental results show that the new fusion algorithm proposed in this paper can not only effectively solve the problem of non-continuous curvature and excessive turning angle at the turning points of the path planned by jump-A * algorithm, but also improve the smoothness of the path and the global optimality. This research is beneficial to the motion control of robots and has certain reference for robot navigation.INDEX TERMS Dynamic window method, jump-A * algorithm, jumping point search, path planning.

In this study, yeast and acetic acid bacteria strains were adopted to enhance the ethanol-type fermentation resulting to a volatile fatty acids yield of 30.22 g/L, and improve acetic acid production to 25.88 g/L, with food wastes as substrate. In contrast, only 12.81 g/L acetic acid can be obtained in the absence of strains. The parameters such as pH, oxidation reduction potential and volatile fatty acids were tested and the microbial diversity of different strains and activity of hydrolytic ferment were investigated to reveal the mechanism. The optimum pH and oxidation reduction potential for the acetic acid production were determined to be at 3.0-3.5 and -500 mV, respectively. Yeast can convert organic matters into ethanol, which is used by acetic acid bacteria to convert the organic wastes into acetic acid. The acetic acid thus obtained from food wastes micro-aerobic fermentation liquid could be extracted by distillation to get high-pure acetic acid.

Influenced by light reflection and water fog interference, ship infrared images are mostly blurred and have low signal-tonoise ratio. In this paper, an improved adaptive Canny edge detection algorithm for infrared image of ship is proposed, which aims to solve the threshold of the traditional Canny cannot be adjusted automatically and the shortcomings of sensitivity to noise. The contrast limited adaptive histogram equalization algorithm is adopted to enhance the infrared image, the morphological filter replaces the Gauss filter to smooth the image, and the OTSU algorithm is utilized to adjust the high and low thresholds dynamically. The experimental results show that the improved Canny algorithm, which can not only improve the contrast of the image and automatically adjust the threshold but also reduce the background sea clutter and false edges, is an effective edge detection method.