Aiming at the low accuracy of lake contour extraction from two-dimensional images of the existing algorithms for analyzing the geometric information of lakes, a lake extraction algorithm based on three-dimensional convolutional neural network was proposed. Firstly, based on the flatness information, the candidate lakes were located from the laser scanning point clouds, and the candidate points were organized as voxels to be an input of the neural network. Meanwhile, the non-lake areas were filtered from candidate areas by the deep learning technique. Then, based on the chain-code algorithm, contours of lakes were extracted from point clouds and their geometry information was analyzed. The experimental results show that, the accuracy of the proposed algorithm in extracting lakes from laser scanning point clouds is 96.34%, and compared with the existing extraction algorithm for two-dimensional images, the proposed algorithm can calculate and analyze the shape information of lakes, which provides convenience for lake monitoring and management.

To deal with the difficulty and low performance of emergency crowd evacuation in public spaces, a crowd evacuation method using robots based on the social force model was proposed. A new human-robot social force model based on the original social force model was first developed, where the human-robot interaction from robots to pedestrians was added to the original social force model. And then, a new method using robot based on the human-robot social force model was presented to evacuate the crowd. After joining the crowd evacuation scenes, the robots can influence the motion of the surrounding pedestrians and reduce the pressure among the pedestrians by moving in the crowd, thus increasing the crowd motion speed and improving the efficiency of crowd evacuation. Two classical scenarios, including a group of crowd escaping from a closed environment and two groups of crowd moving to each other by crossing, were designed and simulated to test the proposed method, and the crowd evacuation method without robots was used for comparison. The experimental results demonstrate that the proposed method based on human-robot social force model can obviously increase the crowd motion speed and improve the efficiency of crowd evacuation.