Fast initial localization method based on particle filter and robot equipment
A particle filter and initial positioning technology, applied in the field of robotics and navigation, can solve the problems of initialization position limitation, inaccurate initial position, inaccurate initialization parameters of particle filter, etc., and achieve the effect of accurate initial position estimation
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Embodiment 1
[0040] figure 1 A flow chart of Embodiment 1 of a fast initial positioning method based on a particle filter in the present invention is shown, including:
[0041] Step 1. Create a grid map.
[0042] Methods for building grid maps include: based on laser or vision sensors, robots move autonomously or users control robots to build maps in the working environment.
[0043] Step 2. Create grid map partitions.
[0044] The method of establishing grid map partitions includes: the program automatically establishes uniform partitions, such as square areas, supports the user to specify the side length of the square area, and the program calculates the distribution mean and variance of each partition.
[0045] The method for establishing grid map partitions also includes: the user defines partitions based on the grid map, such as partitioning according to important landmarks in the grid map, and the program calculates the distribution mean and variance of each partition.
[0046] St...
Embodiment 2
[0056] figure 2 A schematic structural diagram of a robot device for fast initial positioning based on a particle filter of the present invention, including:
[0057]A grid map building module, used to create a grid map;
[0058] A grid map partition module, used to create a grid map partition;
[0059] The initial location area specification module is used to specify the initial location area for the robot, which can be one or more grid map partitions;
[0060] The particle filter initialization module is used for the robot to initialize the particle filter parameters according to the initial position area;
[0061] The particle filter execution module is used for the iterative update of the particle filter, including the sampling particle generation process and the importance sampling process; when the iteration termination condition is reached, the iterative update is stopped and the initial position information of the robot is output.
[0062] For specific details of e...
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