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A slam method based on rodent model and rtab-map loop-closed detection algorithm

A closed-loop detection and animal model technology, applied in the field of bionics and machine vision, can solve the problems of not being able to meet the real-time requirements of closed-loop detection and low efficiency

Active Publication Date: 2018-02-06
光武惠文生物科技(北京)有限公司
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AI Technical Summary

Problems solved by technology

Some closed-loop detection algorithms, such as FAB-MAP and IAB-Map, match the current scene with all historical scenes in real time at each moment, which is inefficient and cannot meet the real-time requirements of closed-loop detection

Method used

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  • A slam method based on rodent model and rtab-map loop-closed detection algorithm
  • A slam method based on rodent model and rtab-map loop-closed detection algorithm
  • A slam method based on rodent model and rtab-map loop-closed detection algorithm

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Embodiment Construction

[0034] Such as figure 1 As shown, local scene cells learn unique scenes in the environment, pose cells formed by merging head direction cells and position cells represent the current position, and the topological experience graph encodes local scene cells and pose cells with nodes and links. The RTAB-Map loop closure detection algorithm uses the local scene cell activity of the RatSLAM system for scene relocation.

[0035] Such as figure 2 As shown, in the RTAB-Map image closed-loop detection method, the unfamiliar scene information is collected first. Since the continuous images captured have a large part of similar content, the continuous image information can be collected by setting the threshold to know the information contained in the current scene. information, store the words from the current position to a certain time in the past in the short-term memory STM, and select the word with the highest frequency of occurrence in the past time to store in the working memory ...

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Abstract

The invention discloses an SLAM method based on a rodent model and an RTAB-Map closed-loop detection algorithm. Spatial positioning can be performed by means of hippocampal neurons of the rodent model. A new bionic navigation model is constructed according to an existing closed-loop detection RTAB-MAP algorithm. On the condition that high real-time performance of the system is ensured, correction of a long-term accumulated error in a macroenvironment can be realized, and furthermore low navigation stability caused by indoor light change to a certain extent.

Description

technical field [0001] The invention relates to the fields of bionics and machine vision, in particular to a SLAM method based on a rodent model and an RTAB-Map closed-loop detection algorithm. Background technique [0002] Traditional probabilistic algorithms can deal with the ambiguity of the sensor and the environment, have good simultaneous localization and map construction performance, and create high-accuracy, high-precision Cartesian maps, but these methods rarely fully solve the entire map construction and navigation problem . How to solve the entire map construction and navigation in a dynamic and complex environment through other existing technologies has become one of the key issues in the simultaneous positioning and map construction of mobile robots. [0003] Visual odometry only uses adjacent frame images to estimate motion, and there are cumulative errors. Loop-closed detection eliminates cumulative errors through scene relocation, ensuring the global consist...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/02G06T7/73G06N3/08
CPCG05D1/0248G05D1/0274G06N3/088G06T2207/20081G06T2207/20084G06T2207/30252
Inventor 陈孟元许瞳凌有铸
Owner 光武惠文生物科技(北京)有限公司
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