A dynamic detection method to improve SLAM performance

Simultaneous localization and mapping (SLAM) technology is a research hotspot in the field of intelligent mobile robot, and many researchers have developed many classic systems in the past few decades. However, most of the existing SLAM methods assume that the environment of the robot is static, which results in the performance of the system being greatly reduced in the dynamic environment. To solve this problem, a new dynamic object detection method based on point cloud motion analysis is proposed and incorporated into ORB-SLAM2. First, the method is regarded as a preprocessing stage, detecting moving objects in the scene, and then removing the moving objects to enhance the performance of the SLAM system. Experiments performed on a public RGB-D dataset show that the motion cancellation method proposed in this paper can effectively improve the performance of ORB-SLAM2 in a highly dynamic environment.     

一道新教材习题的再思考

向量具有几何代数的双重性,是中学知识网络的重要交汇点,在新教材的教学中,一道习题引起了笔者的注意,笔者对这道题进行深入思考,确保数学核心素养落地生花.