Dynamic particle tree SLAM algorithm based on hierarchical structure

A particle and algorithm technology, applied in the field of dynamic particle tree SLAM algorithm, can solve problems such as measurement error performance degradation, SLAM algorithm update and storage speed are difficult to meet the real-time application requirements of robots, etc., to achieve improved accuracy, efficient navigation and positioning tasks, and meet The effect of real-time requirements

Inactive Publication Date: 2014-07-02
FUDAN UNIV
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AI Technical Summary

Problems solved by technology

Because there are many uncertain factors in the SLAM process, such as environmental interference, measurement error, motion error, and moving obstacles, the performance is degraded, and in the case of input from a large-throughput sensor (such as a laser scanning sensor), the performance of the SLAM algorithm The update and storage speed is difficult to meet the actual real-time application requirements of robots

Method used

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  • Dynamic particle tree SLAM algorithm based on hierarchical structure
  • Dynamic particle tree SLAM algorithm based on hierarchical structure
  • Dynamic particle tree SLAM algorithm based on hierarchical structure

Examples

Experimental program
Comparison scheme
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Embodiment Construction

[0056] The test platform of this system is the Artoo robot developed by the Limb Intelligence Laboratory. The hardware environment involved in this navigation system includes the following two parts (components that have little to do with navigation are omitted here).

[0057] Table 1 Motion unit and sensor parameters

[0058]

[0059] The experiment is carried out in a simulation environment, the scene is indoors, and the overall is a circular corridor. For the clarity of the view, the gray part in the picture is the blank area, and the black part is the obstacle (wall). Figure 7 The map information generated by high-level global operations and low-level local operations during the running process will be listed separately.

[0060] Figure 7 From (a)-(f) in chronological order, between two adjacent pictures, because of the effect of low-level operations, one of the places is updated. and Figure 8 It is the case that the lower level generates a part of the whole env...

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Abstract

The invention belongs to the field of artificial intelligence, and particularly relates to a dynamic particle tree SLAM algorithm based on a hierarchical structure. The stability of the SLAM algorithm can be effectively improved. Probability models are provided with two types of different resolution view angles through the hierarchical structure. On one hand, a global model with the low resolution is beneficial to generation and maintenance of global information, can keep map overlapping and closing and lays a foundation for a navigation system to generate information such as topological graphs; on the other hand, the navigation accuracy in a small area can be well maintained through high-accuracy low-level local information, accumulative errors can not be repeatedly substituted, and it is maintained that errors of the whole algorithm are within the acceptable level range after the algorithm is operated for a long time. The time complexity and the space complexity can be well reduced through a particle tree which is dynamically updated.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, and in particular relates to a hierarchical structure-based dynamic particle tree SLAM algorithm. Background technique [0002] Robotics has developed rapidly since the 1990s. In the field of navigation and positioning, the robot needs to estimate its own position and the entire scene map. For probabilistic modeling, it is difficult to achieve in terms of calculation and operability. Therefore, sampling in statistics is introduced. to accomplish this task. The introduction of the particle filter algorithm has enabled the subsequent navigation algorithms based on the Monte Carlo method to have relatively stable performance in practical applications, especially the introduction of the SLAM (Simultaneous localization and mapping) algorithm, which has made great progress in the robot navigation algorithm. [0003] At present, the robot navigation problem can be divided into two categories: on...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
Inventor 金城杨昭冯瑞薛向阳
Owner FUDAN UNIV
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