Dynamic object removal method based on point cloud features and Monte Carlo extension method

Abstract

The invention discloses a dynamic object removal method based on point cloud features and a Monte Carlo extension method, and solves the problem that a dynamic object appears in an SLAM system. The method comprises the following steps: 1, constructing a point cloud data sample data set, constructing a three-dimensional global coordinate system, and initializing environment information; 2, extracting point cloud data under a global coordinate system, and calculating local curvature, an inertia tensor matrix and a covariance matrix of the point cloud data as point cloud space distribution characteristics; 3, carrying out the preprocessing of a point cloud filter, and removing isolated points and edge points; and 4, innovatively providing a point cloud clustering algorithm from the center to the edge, clustering the preprocessed point cloud data based on the newly designed point cloud clustering algorithm, and determining the contour of the object; 5, using a Monte Carlo method to improve the total probability formula, recurring and calculating the influence weight of the point cloud particles, deducing the clustering object state, removing the dynamic object, and retaining the static object. According to the method, the dynamic information of the moving object in the physical environment is effectively removed, and a real static physical environment is obtained.

Description

technical field [0001] The invention relates to the field of unmanned driving technology, in particular to a dynamic object removal based on point cloud features and Monte Carlo extension method. Background technique [0002] With the rapid development of artificial intelligence technology in the field of mobile robots, especially in the field of unmanned driving technology, it has shown its huge development potential and application value. At the same time, Simultaneous Localization and Mapping (SLAM), as the core technology of unmanned driving, plays an indispensable role in vehicle positioning and navigation. SLAM technology refers to the process in which the subject acquires information through sensors to determine its own pose and construct an environmental map during movement, thereby solving the problem of positioning and mapping when the subject moves in an unknown environment. [0003] Among them, the front-end visual odometry (VO) of SLAM technology and SLAM techn...

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Problems solved by technology

[0005] Aiming at the problems that may arise in related technologies, the present invention proposes a dynamic object removal based on point cloud features and Monte Carlo extension method to solve the problem of low measurement accuracy and efficiency caused by the presence of dynamic objects in the SLAM process

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