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EKF-SLAM (Extended Kalman Filter-Simultaneous Localization And Mapping) algorithm based on straight line feature map

An EKF-SLAM and linear feature technology, applied in the field of mobile robots, can solve the problems of large amount of computation and poor real-time performance, and achieve the effect of low complexity, high positioning accuracy, and obvious linear features

Active Publication Date: 2017-02-22
成都普诺思博科技有限公司
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  • Abstract
  • Description
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  • Application Information

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Problems solved by technology

[0005] The purpose of the present invention is to solve the problem that the EKF-SLAM algorithm in the prior art is calculated based on the spatial point characteristics of the environment, the calculation amount is large, and the real-time performance is poor, and an EKF-SLAM algorithm based on a linear feature map is proposed.

Method used

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  • EKF-SLAM (Extended Kalman Filter-Simultaneous Localization And Mapping) algorithm based on straight line feature map
  • EKF-SLAM (Extended Kalman Filter-Simultaneous Localization And Mapping) algorithm based on straight line feature map
  • EKF-SLAM (Extended Kalman Filter-Simultaneous Localization And Mapping) algorithm based on straight line feature map

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Embodiment Construction

[0019] Embodiments of the present invention will be further described below in conjunction with the accompanying drawings.

[0020] The present invention provides an EKF-SLAM algorithm based on a linear feature map, such as figure 1 shown, including the following steps:

[0021] S1. Straight line feature extraction: the system performs region segmentation and straight line fitting on the data measured by the laser radar, and obtains the parameter equation of the straight line feature.

[0022] In the present invention, environmental features are mainly composed of many segmented line segments, so region segmentation and feature extraction are our main tasks in such a structured environment. The system in the present invention refers to the mobile robot platform system.

[0023] First of all, we analyze the information directly obtained from the data scanned by the lidar. There are some points in the lidar data that will interfere with the extraction of our straight line feat...

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Abstract

The invention discloses an EKF-SLAM (Extended Kalman Filter-Simultaneous Localization And Mapping) algorithm based on a straight line feature map, which is characterized in that straight line features in an environment are extracted by using laser radar, and a feature map is established according to the straight line features. The EKF-SLAM algorithm taking a straight line as the feature map is creatively designed. In an experimental environment with obvious straight line features, straight lines features of the environment are extracted very easily. The complexity of the algorithm is low, the operation overhead of a processor is reduced, the real-time performance of the system is improved, and the environment processing means of the SLAM algorithm is enriched.

Description

technical field [0001] The invention belongs to the technical field of mobile robots, and in particular relates to the design of an EKF-SLAM algorithm based on a linear feature map. Background technique [0002] With the development of robot technology, the application of robots is more and more extensive, and it penetrates into almost all fields. Mobile robots are an important branch of robotics. According to their structure, they can generally be divided into wheeled, legged, crawler, suction cup and composite robots. Among them, wheeled mobile robots are widely used due to their simple control, stable motion and high energy utilization. [0003] Nowadays, the map building and navigation of mobile robots is a hot research topic in this field. SLAM (Simultaneous Localization And Mapping) refers to the problem of simultaneous localization and map creation of mobile robots, also known as CLM (Concurrent Mapping and Localization). The SLAM problem can be described as: in a t...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/0223G05D1/0257G05D1/0274
Inventor 张鹏飞何俐萍吴家敏肖立超孙家弼
Owner 成都普诺思博科技有限公司
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