CN114154117B - SLAM method - Google Patents

SLAM method Download PDF

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CN114154117B
CN114154117B CN202111532176.8A CN202111532176A CN114154117B CN 114154117 B CN114154117 B CN 114154117B CN 202111532176 A CN202111532176 A CN 202111532176A CN 114154117 B CN114154117 B CN 114154117B
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任杰
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Metoak Technology Beijing Co ltd
Yuanxiang Technology Suzhou Co ltd
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Abstract

The invention discloses a SLAM method; belongs to the field of synchronous positioning and map construction of a movable platform; the technical key points are as follows: abstracting and expressing images received by machine vision into different levels of information; the higher the information single memory space of the higher layer is, the higher the information single memory space of the lower layer is; the higher the information number of the layer is, the more; the lower layers have fewer information numbers. By adopting the high-efficiency long-time large-scale SLAM method, the performance and the high efficiency of loop detection under the long-time large-scale SLAM are achieved.

Description

SLAM method
The application is a divisional application, the application number of the original application is 202110658243.4, the application date is 2021, 6 months and 15 days, and the invention name is 'an efficient long-time large-scale SLAM method and system'.
Technical Field
The invention relates to the technical field of automobile synchronous positioning and map construction, in particular to an SLAM method.
Background
SLAM, an acronym for Simultaneous localization and Mapping, which is interpreted as: synchronous positioning and map construction; the technology is a core technology (which belongs to support software in the field of intelligent transportation) for realizing autonomous navigation positioning and building an environment map for an automobile.
The existing Visual SLAM algorithm faces the main problem that a large amount of historical information needs to be stored to carry out Loop Detection (Loop Closure Detection) in a larger scale and a longer time range to reduce accumulated deviation when facing Long-term (Long-term) and large-scale (Large-scale) scenes.
For example, CN111767854A proposes a SLAM loop detection method combining scene text semantic information, which has the core steps of: for any key frame in the key frame set, calculating the cosine similarity of the total information vector and the current frame total information vector, and taking the key frame of which the similarity is greater than a certain threshold and which is not directly adjacent to the current frame as a loop candidate frame. As this approach, there is the aforementioned problem of storing information vectors for each key frame. This is very stressful for hardware storage devices.
Disclosure of Invention
The invention aims to provide an SLAM method, which solves the defects in the prior art.
A SLAM method comprising the steps of:
abstracting and expressing images received by machine vision into information of different levels;
the higher the information individual storage amount, the higher the information individual storage amount of the lower layer (i.e., X) j，β The storage space occupied by a single is less than X j+1，β A single occupied storage space);
the higher the information number of the layer is, the more; the lower the layer, the less the information number (i.e., Q described below) j >Q j+1 )。
An efficient long-time large-scale SLAM method comprises the following steps:
s100, establishing an information hierarchy sequence of the key frames:
the information hierarchy sequence of the key frame is expressed as follows according to the descending order of the hierarchy level by level: level 1 information, level 2 information, level j information … … …, level k information:
s200, determining the storage capacity of each information level of the key frame:
the storage amount of the 1 st level information is Q 1 The storage amount of the 2 nd level information is Q 2 … … … … the storage capacity of the j level information is Q j … … … … the k-th level information has a storage capacity of Q k ：
For Q 1 ～Q k For example, there are: q 1 >Q 2 >……Q j-1 >Q j >……Q k ；
S300, the current key frame is the Yth key frame, and the current key frame is extracted from the Yth key frameTaking the information of the 1 st to k layers: x 1，Y 、X 2，Y 、……X j，Y 、……X k，Y (ii) a And simultaneously calculating the storage importance coefficients of the information of the 1 st to k th layers extracted from the Yth key frame: z 1，Y 、Z 2，Y 、……Z j，Y 、……Z k，Y ；
X 1，Y 、X 2，Y 、……X j，Y 、……X k，Y Respectively represent: level 1 information of the Y-th key frame, level 2 information of the Y-th key frame, … … level j information of the Y-th key frame, … … level k information of the Y-th key frame;
Z 1，Y 、Z 2，Y 、……Z j，Y 、……Z k，Y respectively represent: a storage importance coefficient of the 1 st level information of the Yth key frame, a storage importance coefficient of the 2 nd level information of the Yth key frame, a storage importance coefficient of the j th level information of the … … th key frame, a storage importance coefficient of the k th level information of the … … th key frame;
s400, the storage importance coefficients of the information of the 1 st to k th layers extracted from the current Y-th key frame are: z is a linear or branched member 1，Y 、Z 2，Y 、……Z j，Y 、……Z k，Y Adding the importance parameter into a storage importance coefficient matrix of the current key frame level information (all the storage importance parameters of the extracted 1 st-k level information of the Y-th key frame are stored into the storage importance coefficient matrix of the current key frame level information);
S500，
extracting the information of the 1 st to k th layers from the current Y-th key frame: x 1，Y 、X 2，Y 、……X j，Y 、……X k，Y， Adding the key frame level information into a current key frame level information matrix:
when 0 is present<Y≤Q k When the current key frame set is selected, all the extracted 1 st-k level information of the Y key frame is stored into the current key frame set;
the above steps are expressed as follows:
Figure BDA0003411190870000021
X j，I expressing j level information of the I key frame;
when Q is j <Y≤Q j-1 When j represents any natural number from 2 to k;
storing all the level information from level 1 to level j-1 of the Y key frame into the current key frame set, wherein the steps are expressed by adopting the following formula:
Figure BDA0003411190870000031
for the j-th to k-th level information of the Y-th key frame, calculating layer by layer to determine whether to store:
for any of the j-th to k-th layers:
first, from Z β,1 ,Z β,2 ……Z β,I ……Z β,Y-1 Finding the minimum value, which takes Z β,m The information storage importance parameter of the mth key frame beta level is minimum;
secondly, according to Z β,m 、Z β,Y Determines whether to store the beta-level information X of the Yth key frame β,Y ：
When Z is β,m >Z β,Y
Then Z β,Y Given a new value such that Z β,Y No longer participate in the ranking;
X β,Y giving a new value of NULL or 0, namely not storing the beta level information of the Yth key frame;
when Z is β,m ≤Z β,Y
Then Z β,m Given a new value such that Z β,m No longer participate in the ranking;
X β,m assigning a new value of NULL or 0, i.e., deleting the beta level information of the mth key frame and adding the beta level information X of the Yth key frame β,Y Storing, i.e. storing, the beta-th of the mth key frameThe storage space of the hierarchy information is allowed to be equal to the storage space of the beta hierarchy information of the Y key frame, namely the storage quantity of the beta hierarchy information is always kept at Q β ；
When Q is 1 <When Y is in the range of:
for the level 1-k information of the Y key frame, calculating layer by layer to determine whether to store:
for any of the 1 st to k th layers,
first, from Z β,1 ,Z β,2 ……Z β,I ……Z β,Y-1 Finding the minimum value, which takes Z β,m The information storage importance parameter of the mth key frame beta level is minimum;
secondly, according to Z β,m 、Z β,Y Determines whether to store the beta-level information X of the Yth key frame β,Y ：
When Z is β,m >Z β,Y
Then Z β,Y Given a new value such that Z β,Y No longer participate in the ranking;
X β,Y giving a new value of NULL or 0, namely not storing the beta level information of the Yth key frame;
when Z is β,m ≤Z β,Y
Then Z β,m Given a new value such that Z β,m No longer participate in the ranking;
X β,m assigning a new value of NULL or 0, i.e., deleting the beta level information of the mth key frame and adding the beta level information X of the Yth key frame β,Y Storing, namely, the storage space of the beta level information of the mth key frame is reserved to the storage space of the beta level information of the Yth key frame, namely, the storage space of the beta level information is always kept at Q β 。
Further, "when Z" in step S500 β,m >Z β,Y ，Z β,Y New values are assigned ", NULL or + ∞.
Further, in step S100, k is not less than 4.
The invention has the beneficial effects that:
first, the basic idea of the present application is: abstracting and expressing information received by machine vision at different semantic levels, and coding the information from the information level; the higher the semantic feature of the higher layer is, the more simplified the macro information quantity is, the higher the extraction frequency is, the longer the time stored in the SLAM system is; conversely, the lower the level of the point cloud feature, the larger the amount of data stored, the lower the frequency of extraction, and the shorter the time for storage in the SLAM system. By setting different storage and retrieval index configurations, the performance and the efficiency of freely allocating storage/retrieval and long-time large-scale SLAM loop detection are achieved.
Secondly, based on the basic concept of the application, a method for storing the SLAM key frame matrix is provided: the storage is determined by means of a double coefficient, namely: and storing the importance coefficient matrix and the current key frame level information matrix to jointly determine how the newly acquired 1 st-k level information of the Y-th key frame is stored into the current key frame level information matrix.
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The invention will be further described in detail with reference to examples of embodiments shown in the drawings to which, however, the invention is not restricted.
FIG. 1 is a diagram of a sequence of information levels according to the first embodiment.
Fig. 2 is a schematic diagram of "original image-dense point cloud feature" extraction according to the first embodiment.
Detailed Description
An efficient long-time large-scale SLAM method comprises the following steps:
s100, establishing an information hierarchy sequence of the key frames:
the information hierarchy sequence of the key frame is expressed as follows according to the descending order of the hierarchy level by level: level 1 information, level 2 information, level j information … … …, level k information:
s200, determining the storage quantity of each information level of the key frame:
the storage amount of the 1 st level information is Q 1 The storage amount of the 2 nd level information is Q 2 … … … … j-th information storageIs Q j … … … … the k-th level information has a storage capacity of Q k ：
For Q 1 ～Q k For example, there are: q 1 >Q 2 >……Q j-1 >Q j >……Q k ；
S300, the current key frame is the Yth key frame, and the information of layers 1 to k is extracted from the Yth key frame: x 1，Y 、X 2，Y 、……X j，Y 、……X k，Y (ii) a And simultaneously calculating the storage importance coefficients of the information of the 1 st to k th layers extracted from the Yth key frame: z 1，Y 、Z 2，Y 、……Z j，Y 、……Z k，Y ；
X 1，Y 、X 2，Y 、……X j，Y 、……X k，Y Respectively represent: level 1 information of the Y-th key frame, level 2 information of the Y-th key frame, … … level j information of the Y-th key frame, … … level k information of the Y-th key frame;
Z 1，Y 、Z 2，Y 、……Z j，Y 、……Z k，Y respectively represent: a storage importance coefficient of level 1 information of a Y-th key frame, a storage importance coefficient of level 2 information of the Y-th key frame, a storage importance coefficient of a j-th level information of … … the Y-th key frame, a storage importance coefficient of a k-th level information of … … the Y-th key frame;
s400, the storage importance coefficients of the information of the 1 st to k th layers extracted from the current Y-th key frame are: z 1，Y 、Z 2，Y 、……Z j，Y 、……Z k，Y Adding the importance parameter into a storage importance parameter set (namely, adding the importance parameter set into a storage importance coefficient matrix of the hierarchy information of the current key frame) of the current key frame (at the moment, the corresponding current key frame has 1 st to Y-1 st key frames):
all storage importance parameters of the extracted 1 st-k level information of the Y-th key frame are stored into a storage importance coefficient matrix of the current key frame level information;
the above steps can be expressed as follows:
Figure BDA0003411190870000051
S500，
extracting the information of the 1 st to k th layers from the current Y-th key frame: x 1，Y 、X 2，Y 、……X j，Y 、……X k，Y， Add to the current key frame set (i.e., to the current key frame level information matrix):
k when 0 is present<When Y is less than or equal to QStoring all the extracted 1 st-k level information of the Y-th key frame into the current key frame set;
the above steps can be expressed as follows:
Figure BDA0003411190870000052
X j，I information of j level expressing the I key frame (the meaning of other expressions can be known from it, for example, X k，Y K-th level information expressed as the Y-th key frame).
k k-1 When Q is<When Y is less than or equal to QAnd storing all the level information from level 1 to level k-1 of the Y-th key frame into the current key frame set, wherein the steps can be expressed as follows:
Figure BDA0003411190870000061
for the kth layer information of the Y-th key frame:
first, from Z k,1 ,Z k,2 ……Z k,I ……Z k,Y-1 Finding the minimum value, which takes Z k,m The information storage importance parameter of the kth level of the mth key frame is minimum;
second, according to Z k,m 、Z k,Y Determines whether to store the kth level information X of the Yth key frame k,Y ：
When Z is k,m >Z k,Y
Then Z k,Y Assigning a new value (e.g., NULL or + ∞) (so that Z k,Y No longer participating in the ranking);
X k,Y giving a new value of NULL or 0, namely not storing the kth level information of the Yth key frame;
when Z is k,m ≤Z k,Y
Then Z k,m Given a new value such that Z k,m No longer participate in the ranking;
X k,m assigning a new value of NULL or 0, i.e. removing the kth level information of the mth key frame and adding the kth level information X of the Yth key frame k,Y Storing, namely, the storage space of the k level information of the mth key frame is saved to the storage space of the k level information of the Yth key frame (namely, the storage amount of the k level information is always kept at Q) k )。
……
j j-1 When Q is<When Y is less than or equal to QAnd storing all the level information from level 1 to level j-1 of the Y-th key frame into the current key frame set, wherein the steps can be expressed as follows:
Figure BDA0003411190870000062
for j-k level (it should be noted that j in this application represents any natural number between [1, k ], but not k-1, i.e. the sequence of j, k in english does not represent the distance between the two) information of the Y-th key frame, calculating layer by layer to determine whether to store:
for the jth level information of the yth key frame:
first, from Z j,1 ,Z j,2 ……Z j,I ……Z j,Y-1 Finding the minimum value, which takes Z j,m The j level information storage importance parameter of the mth key frame is minimum;
second, it is used forAccording to Z j,m 、Z j,Y Determines whether to store the j level information X of the Y key frame j,Y ：
When Z is j,m >Z j,Y
Then Z j,Y Assigning a new value (e.g., NULL or + ∞) such that Z j,Y No longer participate in the ranking;
X j,Y giving a new value of NULL or 0, namely not storing the j level information of the Y key frame;
when Z is j,m ≤Z j,Y
Then Z j,m Given a new value such that Z j,m No longer participate in the ranking;
X j,m assigning a new value of NULL or 0, i.e. deleting the j level information of the mth key frame and adding the j level information X of the Yth key frame j,Y Storing, namely, the storage space of the j level information of the mth key frame is made to be equal to the storage space of the j level information of the Yth key frame (namely, the storage amount of the j level information is always kept at Q j )。
For the j +1 th level information of the Y-th key frame:
first, from Z j+1,1 ,Z j+1,2 ……Z j+1,I ……Z j+1,Y-1 Finding the minimum value, which takes Z j+1,m The j +1 th level information storage importance parameter of the mth key frame is minimum;
secondly, according to Z j+1,m 、Z j+1,Y Determines whether to store the j +1 th level information X of the Yth key frame j+1,Y ：
When Z is j+1,m >Z j+1,Y
Then Z j+1,Y Assigning a new value (e.g., NULL or + ∞) such that Z j+1,Y No longer participate in the ranking;
X j+1,Y giving a new value of NULL or 0, namely not storing the j +1 level information of the Yth key frame;
when Z is j+1,m ≤Z j+1,Y
Then Z j+1,m Given a new value such that Z j+1,m No longer participate in the ranking;
X j+1,m assigning a new value of NULL or 0, i.e. removing the j +1 level information of the mth key frame and deleting the j +1 level information X of the Yth key frame j+1,Y Storing, namely, the storage space of the j +1 level information of the mth key frame is made to be equal to the storage space of the j +1 level information of the Yth key frame (namely, the storage amount of the j +1 level information is always kept at Q j+1 )。
………
For the kth layer information of the Yth key frame:
first, from Z k,1 ,Z k,2 ……Z k,I ……Z k,Y-1 Find the minimum value, which takes Z k,m The information storage importance parameter of the kth level of the mth key frame is minimum;
secondly, according to Z k,m 、Z k,Y Determines whether to store the kth level information X of the Yth key frame k,Y ：
When Z is k,m >Z k,Y
Then Z k,Y Assigning a new value (e.g., NULL or + ∞) (so that Z k,Y No longer participating in the ranking);
X k,Y giving a new value of NULL or 0, namely not storing the kth level information of the Yth key frame;
when Z is k,m ≤Z k,Y
Then Z k,m Given a new value such that Z k,m No longer participate in the ranking;
X k,m assigning a new value of NULL or 0, i.e. removing the kth level information of the mth key frame and adding the kth level information X of the Yth key frame k,Y Storing, namely, the storage space of the k-level information of the mth key frame is saved to the storage space of the k-level information of the Yth key frame (namely, the storage amount of the k-level information is always kept at Q k )。
……
2 1 When Q is<When Y is less than or equal to Q，
Storing all the level 1 information of the Y-th key frame into the current key frame set, wherein the steps can be expressed as follows:
|X 1，1 X 1，2 ......X 1，I ......X 1，Y-1 |—>|X 1，1 X 1，2 ......X 1，I ......X 1，Y-1 X 1，Y |
for the 2 nd to k th level information of the Y key frame, calculating layer by layer to determine whether to store:
for the level 2 information of the Yth key frame:
first, from Z 2,1 ,Z 2,2 ……Z 2,I ……Z 2,Y-1 Finding the minimum value, which takes Z 2,m To indicate that the storage importance parameter of the mth key frame level 2 information is minimum;
secondly, according to Z 2,m 、Z 2,Y Determines whether to store the 2 nd level information X of the Yth key frame 2,Y ：
When Z is 2,m >Z 2,Y
Then Z 2,Y Assigning a new value (e.g., NULL or + ∞) such that Z 2,Y No longer participate in the ranking;
X 2,Y giving a new value of NULL or 0, namely not storing the 2 nd level information of the Yth key frame;
when Z is 2,m ≤Z 2,Y
Then Z 2,m Given a new value such that Z 2,m No longer participate in the ranking;
X 2,m assigning a new value of NULL or 0, i.e., deleting the 2 nd level information of the mth key frame and deleting the 2 nd level information X of the Yth key frame 2,Y Storing, namely, the storage space of the 2 nd level information of the mth key frame is saved to the storage space of the 2 nd level information of the Yth key frame (namely, the storage amount of the 2 nd level information is always kept at Q 2 )。
For the level 3 information of the Yth key frame:
first, from Z 3,1 ,Z 3,2 ……Z 3,I ……Z 3,Y-1 Find the minimum value, which takes Z 3,m To indicate that the 3 rd level information storage importance parameter of the mth key frame is minimum;
second, according to Z 3,m 、Z 3,Y Determines whether to store the 3 rd level information X of the Yth key frame 3,Y ：
When Z is 3,m >Z 3,Y
Then Z 3,Y Assigning a new value (e.g., NULL or + ∞) such that Z 3,Y No longer participate in the ranking;
X 3,Y giving a new value of NULL or 0, namely not storing the 3 rd level information of the Yth key frame;
when Z is 3,m ≤Z 3,Y
Then Z 3,m Given a new value such that Z 3,m No longer participate in the ranking;
X 3,m assigning a new value of NULL or 0, i.e., deleting the 3 rd level information of the mth key frame and deleting the 3 rd level information X of the Yth key frame 3,Y Storing, namely, the storage space of the 3 rd level information of the mth key frame is saved to the 3 rd level information storage space of the Yth key frame (namely, the storage amount of the 3 rd level information is always kept at Q 3 )。
………
For the kth layer information of the Y-th key frame:
first, from Z k,1 ,Z k,2 ……Z k,I ……Z k,Y-1 Finding the minimum value, which takes Z k,m The information storage importance parameter of the kth level of the mth key frame is minimum;
secondly, according to Z k,m 、Z k,Y Determines whether to store the kth level information X of the Yth key frame k,Y ：
When Z is k,m >Z k,Y
Then Z k,Y Assigning a new value (e.g., NULL or + ∞) (so that Z k,Y No longer participating in the ranking);
X k,Y giving a new value of NULL or 0, namely not storing the kth level information of the Yth key frame;
when Z is k,m ≤Z k,Y
Then Z k,m Given a new value such that Z k,m No longer participate in the ranking;
X k,m assigning a new value of NULL or 0, i.e. removing the kth level information of the mth key frame and adding the kth level information X of the Yth key frame k,Y Storing, namely, the storage space of the k-level information of the mth key frame is saved to the storage space of the k-level information of the Yth key frame (namely, the storage amount of the k-level information is always kept at Q k )。
1 When Q is<At Y time：
For the level 1-k information of the Y key frame, calculating layer by layer, and determining whether to store:
for level 1 information of the Yth key frame:
first, from Z 1,1 ,Z 1,2 ……Z 1,I ……Z 1,Y-1 Finding the minimum value, which takes Z 1,m The 1 st level information storage importance parameter of the mth key frame is minimum;
secondly, according to Z 1,m 、Z 1,Y Determines whether to store the level 1 information X of the Yth key frame 1,Y ：
When Z is 1,m >Z 1,Y
Then Z 1,Y Assigning a new value (e.g., NULL or + ∞) such that Z 1,Y No longer participate in the ranking;
X 1,Y giving a new value of NULL or 0, namely, not storing the level 1 information of the Yth key frame;
when Z is 1,m ≤Z 1,Y
Then Z 1,m Given a new value such that Z 1,m No longer participate in the ranking;
X 1,m assigning a new value of NULL or 0, i.e. deleting the level 1 information of the mth key frame and assigning the Yth key frameLevel 1 information X of key frame 1,Y Storing, namely, the storage space of the 1 st level information of the mth key frame is saved to the 1 st level information storage space of the Yth key frame (namely, the storage amount of the 1 st level information is always kept at Q 1 )。
For the level 2 information of the Y-th key frame:
first, from Z 2,1 ,Z 2,2 ……Z 2,I ……Z 2,Y-1 Finding the minimum value, which takes Z 2,m To indicate that the storage importance parameter of the mth key frame level 2 information is minimum;
second, according to Z 2,m 、Z 2,Y Determines whether to store the 2 nd level information X of the Yth key frame 2,Y ：
When Z is 2,m >Z 2,Y
Then Z 2,Y Assign a new value (e.g., NULL or + ∞) such that Z 2,Y No longer participate in the ranking;
X 2,Y giving a new value of NULL or 0, namely not storing the 2 nd level information of the Yth key frame;
when Z is 2,m ≤Z 2,Y
Then Z 2,m Given a new value such that Z 2,m No longer participate in the ranking;
X 2,m assigning a new value of NULL or 0, i.e., deleting the 2 nd level information of the mth key frame and deleting the 2 nd level information X of the Yth key frame 2,Y Storing, namely, the storage space of the 2 nd layer information of the mth key frame is saved to the storage space of the 2 nd layer information of the Yth key frame (namely, the storage amount of the 2 nd layer information is always kept at Q 2 )。
For the level 3 information of the Yth key frame:
first, from Z 3,1 ,Z 3,2 ……Z 3,I ……Z 3,Y-1 Finding the minimum value, which takes Z 3,m To indicate that the 3 rd level information storage importance parameter of the mth key frame is minimum;
secondly, according to Z 3,m 、Z 3,Y Determines whether to store the 3 rd level information X of the Yth key frame 3,Y ：
When Z is 3,m >Z 3,Y
Then Z 3,Y Assigning a new value (e.g., NULL or + ∞) such that Z 3,Y No longer participate in the ranking;
X 3,Y assigning a new value of NULL or 0, i.e. not storing the level 3 information of the Yth key frame;
when Z is 3,m ≤Z 3,Y
Then Z 3,m Given a new value such that Z 3,m No longer participate in the ranking;
X 3,m assigning a new value of NULL or 0, i.e., removing the 3 rd level information of the mth key frame and adding the 3 rd level information X of the yth key frame 3,Y Storing, namely, the storage space of the 3 rd level information of the mth key frame is saved to the 3 rd level information storage space of the Yth key frame (namely, the storage space of the 3 rd level information is always kept at Q 3 )。
………
For the kth layer information of the Y-th key frame:
first, from Z k,1 ,Z k,2 ……Z k,I ……Z k,Y-1 Finding the minimum value, which takes Z k,m The information storage importance parameter of the kth level of the mth key frame is minimum;
secondly, according to Z k,m 、Z k,Y Determines whether to store the kth level information X of the Yth key frame k,Y ：
When Z is k,m >Z k,Y
Then Z k,Y Assigning a new value (e.g., NULL or + ∞) (so that Z k,Y No longer participating in the ranking);
X k,Y giving a new value of NULL or 0, namely not storing the kth level information of the Yth key frame;
when Z is k,m ≤Z k,Y
Then Z k,m Given a new value such that Z k,m No longerParticipating in sorting;
X k,m assigning a new value of NULL or 0, i.e. removing the kth level information of the mth key frame and adding the kth level information X of the Yth key frame k,Y Storing, namely, the storage space of the k-level information of the mth key frame is saved to the storage space of the k-level information of the Yth key frame (namely, the storage amount of the k-level information is always kept at Q k )。
An efficient long-term large-scale SLAM system comprising: the system comprises an information level sequence establishing module, an information level memory space establishing module, a current key frame information extracting module, a current key frame information storage importance coefficient calculating module and a key frame set level information storage importance coefficient calculating and storing module; a key frame set level information calculation and storage module;
the information level sequence establishing module and the information level storage quantity establishing module are respectively connected with the current key frame information extracting module;
the information level sequence establishing module and the information level storage capacity establishing module are respectively connected with the current key frame information storage importance coefficient calculating module;
the current key frame information storage importance coefficient calculation module is connected with the key frame set level information storage importance coefficient calculation and storage module;
the current key frame information extraction module and the key frame set level information storage importance coefficient calculation and storage module are respectively connected with the key frame set level information calculation and storage module;
the information level sequence establishing module is used for establishing an information level sequence of a key frame set and guiding the current key frame information extracting module to extract information of a current key frame image, and is a carrier operated in the step S100;
the information level storage quantity establishing module is used for establishing different level information storage spaces of the key frame set and is a carrier operated in the step S200;
the current key frame information extraction module is used for extracting information of different levels from the current key frame image, and is a carrier operated in the step S300;
the current key frame information storage importance coefficient calculation module is used for calculating storage importance coefficients of different levels of information of the current key frame;
the key frame set level information storage importance coefficient calculation and storage module is used for storing the storage importance coefficients of different level information of the current key frame set;
the key frame set level information calculation and storage module is used for determining a storage mode (namely determining whether the key frame set level information is stored) for extracting information of different levels from the current key frame image transmitted by the current key frame information extraction module.
It should be noted that: the information level sequence establishing module and the information level storage capacity establishing module are not necessary technical features, that is, the S100 and the S200 are not necessarily set by the two modules, and a designer can directly set related parameters in the software system.
The first embodiment is as follows: as shown in fig. 1, an efficient long-term large-scale SLAM method performs hierarchical processing on information of a key frame set; the method comprises the following steps:
s100, establishing an information level sequence of the key frame set:
level 1 information, namely a characteristic word set (namely a BOW model) of a scene;
level 2 information: spatial relationship expression of spatial entities;
level 3 information: point/line/surface features;
level 4 information: dense point cloud features.
S200, establishing the storage priority of the information of the key frame set according to the information level sequence established in the step S100: the storage amount of the information level of the hierarchy is larger than that of the information level of the hierarchy, and the storage time of the information level of the hierarchy is longer than that of the information level of the hierarchy.
Specifically, S200 is to determine the storage capacity of the 1 st to 4 th information levels of the key frame:
of level 1 informationThe memory capacity is Q 1 The amount of storage of the 2 nd level information is Q50000 2 40000, the storage amount of the 3 rd level information is Q 3 10000, the storage amount of the 4 th hierarchy information is Q 4 ＝700：
S300, the current key frame is the Y-th key frame, as shown in fig. 1: extracting information of layers 1-4 from the Yth key frame: x 1，Y 、X 2，Y 、X 3，Y 、X k，Y ；
And simultaneously calculating the storage importance coefficients of the information of the 1 st to k th layers extracted from the Yth key frame: z 1，Y 、Z 2，Y 、Z 3，Y 、Z k，Y (ii) a The calculation principle of the storage importance coefficient can be specifically determined and adjusted by a system designer according to actual requirements and environments. For example: i am giving the machine in an indoor simulated environment a design of: the storage importance coefficient of the crossroad is positioned by 1.0, the storage importance coefficient of the T-shaped crossroad is positioned by 0.8, and the storage importance coefficient of the middle of the road is positioned by 0.5.
X 1，Y 、X 2，Y 、X 3，Y 、X 4，Y Respectively represent: level 1 information of a Y-th key frame, level 2 information of the Y-th key frame, level 3 information of the Y-th key frame, and level 4 information of the Y-th key frame;
Z 1，Y 、Z 2，Y 、Z 3，Y 、Z 4，Y respectively represent: the storage importance coefficient of the 1 st level information of the Y-th key frame, the storage importance coefficient of the 2 nd level information of the Y-th key frame, the storage importance coefficient of the 3 rd level information of the Y-th key frame and the storage importance coefficient of the 4 th level information of the Y-th key frame;
s400, the storage importance coefficient of the information of the 1 st to 4 th layers extracted from the current Y-th key frame is: z 1，Y 、Z 2，Y 、Z 3，Y 、Z 4，Y Adding the importance coefficient into a storage importance coefficient matrix of the current key frame level information:
all storage importance parameters of the extracted 1 st-4 th-level information of the Y-th key frame are stored into a storage importance coefficient matrix of the current key frame level information;
the above steps can be expressed as follows:
Figure BDA0003411190870000131
s500, extracting the information of the 1 st to 4 th layers from the current Y-th key frame: x 1，Y 、X 2，Y 、X 3，Y 、X 4，Y， Adding the key frame into a current key frame level information matrix:
extracting the information of the 1 st to 4 th layers of the current Y-th key frame: x 1，Y 、X 2，Y 、X 3，Y 、X 4，Y， Adding the key frame level information into a current key frame level information matrix:
4 when 0 is present<When Y is less than or equal to QStoring all the extracted level 1-4 information of the Y-th key frame into a current key frame set;
the above steps can be expressed as follows:
Figure BDA0003411190870000132
j j-1 when Q is<When Y is less than or equal to QAnd storing all the level information from level 1 to level j-1 of the Y-th key frame into the current key frame set, wherein the steps can be expressed as follows:
Figure BDA0003411190870000133
for the j-th to 4-th level information of the Y-th key frame, calculating layer by layer, and determining whether to store:
for any of the jth to 4 layers,
first, from Z β,1 ,Z β,2 ……Z β,I ……Z β,Y-1 Finding the minimum value, which takes Z β,m To show that the information storage of the beta level of the mth key frame is importantThe sexual parameter is minimum;
second, according to Z β,m 、Z β,Y Determines whether to store the beta level information X of the Y-th key frame β,Y ：
When Z is β,m >Z β,Y
Then Z β,Y Assigning a new value (e.g., NULL or + ∞) such that Z β,Y No longer participate in the ranking;
X β,Y giving a new value of NULL or 0, namely not storing the beta level information of the Yth key frame;
when Z is β,m ≤Z β,Y
Then Z β,m Given a new value such that Z β,m No longer participate in the ranking;
X β,m assigning a new value of NULL or 0, i.e., deleting the beta-level information of the mth key frame and adding the beta-level information X of the Yth key frame β,Y Storing, namely, the storage space of the beta level information of the mth key frame is saved to the storage space of the beta level information of the Yth key frame (namely, the storage space of the beta level information is always kept at Q β )。
1 When Q is<At Y time：
For the level 1-4 information of the Y key frame, calculating layer by layer, and determining whether to store:
for any beta-th layer of the 1 st to 4 th layers,
first, from Z β,1 ,Z β,2 ……Z β,I ……Z β,Y-1 Find the minimum value, which takes Z β,m The information storage importance parameter of the mth key frame beta level is minimum;
secondly, according to Z β,m 、Z β,Y Determines whether to store the beta level information X of the Y-th key frame β,Y ：
When Z is β,m >Z β,Y
Then Z β,Y Assigning a new value (e.g., NULL or + ∞) such that Z β,Y No longer participate in the ranking;
X β,Y giving a new value of NULL or 0, namely not storing the beta level information of the Yth key frame;
when Z is β,m ≤Z β,Y
Then Z β,m Given a new value such that Z β,m No longer participate in the ranking;
X β,m assigning a new value of NULL or 0, i.e., deleting the beta level information of the mth key frame and adding the beta level information X of the Yth key frame β,Y Storing, namely, the storage space of the beta-level information of the mth key frame is saved to the storage space of the beta-level information of the Yth key frame (namely, the storage amount of the beta-level information is always kept at Q) β )。
It should be noted that, according to the first embodiment: for any I key frame j layer information X j,I The value is not limited to be a numerical value, that is, it may be a character set, for example, as shown in the first embodiment: x 1，I Is the BOW model data, and may also be a data set, for example: the first embodiment is as follows: x 4，I Is a dense point cloud data set.
The above-mentioned embodiments are only for convenience of description, and are not intended to limit the present invention in any way, and those skilled in the art will understand that the technical features of the present invention can be modified or changed by other equivalent embodiments without departing from the scope of the present invention.

Claims (5)

1. A SLAM method, comprising the steps of:
s100, establishing an information hierarchy sequence of the key frames:
the information hierarchy sequence of the key frame is expressed as follows according to the descending order of the hierarchy level by level: level 1 information, level 2 information, level j information … … …, level k information:
s200, determining the storage quantity of each information level of the key frame:
the storage amount of the 1 st level information is Q 1 The storage amount of the 2 nd level information is Q 2 … … … … the storage capacity of the j level information is Q j … … … … the k-th level information has a storage capacity of Q k ：
For Q 1 ～Q k For example, there are: q 1 >Q 2 >……Q j-1 >Q j >……Q k ；
S300, the current key frame is the Yth key frame, and the information of layers 1 to k is extracted from the Yth key frame: x 1，Y 、X 2，Y 、……X j，Y 、……X k，Y (ii) a And simultaneously calculating the storage importance coefficients of the information of the 1 st to k th layers extracted from the Yth key frame: z is a linear or branched member 1，Y 、Z 2，Y 、……Z j，Y 、……Z k，Y ；
X 1，Y 、X 2，Y 、……X j，Y 、……X k，Y Respectively represent: level 1 information of the Yth key frame, level 2 information of the Yth key frame 、 … … j-th level information of the Y-th key frame 、 … … kth level information of the Yth key frame;
Z 1，Y 、Z 2，Y 、……Z j，Y 、……Z k，Y respectively represent: storage importance coefficient of level 1 information of the Yth key frame, and storage importance coefficient of level 2 information of the Yth key frame 、 … … storage importance coefficient of j level information of Y key frame 、 … … storage importance coefficient of kth level information of the Yth key frame;
s400, the storage importance coefficients of the information of the 1 st to k th layers extracted from the current Y-th key frame are: z 1，Y 、Z 2，Y 、……Z j，Y 、……Z k，Y Adding the key frame level information into a storage importance coefficient matrix of the current key frame level information;
s500, extracting the information of the 1 st to k th layers from the current Y-th key frame: x 1，Y 、X 2，Y 、……X j，Y 、……X k，Y， Adding the key frame level information into a current key frame level information matrix:
when 0 is present<Y≤Q k Then, all the extracted 1 st to k level information of the Y key frame are stored into the current key frame set;
the above steps are expressed as follows:
Figure FDA0003714538800000011
X j，I expressing j level information of the I key frame;
when Q is j <Y≤Q j-1 When j represents any natural number from 2 to k;
storing all the level information from level 1 to level j-1 of the Y key frame into the current key frame set, wherein the steps are expressed by adopting the following formula:
Figure FDA0003714538800000021
for j-th to k-th level information of the Y-th key frame, calculating layer by layer, and determining whether to store:
for any of the j-th to k-th layers:
first, from Z β,1 ,Z β,2 ……Z β,I ……Z β,Y-1 Find the minimum value, which takes Z β,m The information storage importance parameter of the mth key frame beta level is minimum;
second, according to Z β,m 、Z β,Y Determines whether to store the beta level information X of the Y-th key frame β,Y ：
When Z is β,m >Z β,Y
Then Z β,Y Given a new value such that Z β,Y No longer participate in the ranking;
X β,Y assigning a new value of NULL or 0, i.e., not storing the beta-level information of the Yth key frame；
When Z is β,m ≤Z β,Y
Then Z β,m Given a new value such that Z β,m No longer participate in the ranking;
X β,m assigning a new value of NULL or 0, i.e., deleting the beta level information of the mth key frame and adding the beta level information X of the Yth key frame β,Y Storing, namely, the storage space of the beta level information of the mth key frame is reserved to the storage space of the beta level information of the Yth key frame, namely, the storage space of the beta level information is always kept at Q β ；
When Q is 1 <When Y is in the range of:
for the level 1-k information of the Y key frame, calculating layer by layer, and determining whether to store:
for any of the 1 st to k th layers,
first, from Z β,1 ,Z β,2 ……Z β,I ……Z β,Y-1 Finding the minimum value, which takes Z β,m The information storage importance parameter of the mth key frame beta level is minimum;
secondly, according to Z β,m 、Z β,Y Determines whether to store the beta level information X of the Y-th key frame β,Y ：
When Z is β,m >Z β,Y
Then Z β,Y Given a new value such that Z β,Y No longer participate in the ranking;
X β,Y giving a new value of NULL or 0, namely, not storing the beta level information of the Yth key frame;
when Z is β,m ≤Z β,Y
Then Z β,m Given a new value such that Z β,m No longer participate in the ranking;
X β,m assigning a new value of NULL or 0, i.e., deleting the beta level information of the mth key frame and adding the beta level information X of the Yth key frame β,Y Storing, namely, the storage space of the beta level information of the mth key frame is saved to the Yth key frameThat is, the storage amount of the beta-th level information is always kept at Q β 。
2. The SLAM method as claimed in claim 1 wherein step S500 is performed when Z is reached β,m >Z β,Y ，Z β,Y New values are assigned, NULL or + ∞.
3. The SLAM method according to claim 1 or 2, wherein in step S100 k ≧ 4.
4. A SLAM method is characterized in that the information of a key frame set is processed hierarchically; the method comprises the following steps:
s100, establishing an information level sequence of the key frame set:
level 1 information is a characteristic word set of a scene;
level 2 information: spatial relationship expression of spatial entities;
level 3 information: point/line/surface features;
level 4 information: dense point cloud features;
s200, establishing the storage priority of the information of the key frame set according to the information level sequence established in the step S100: the storage capacity of the information level of the high hierarchy is larger than that of the information level of the low hierarchy, and the storage time of the information level of the high hierarchy is longer than that of the information level of the low hierarchy:
the storage amount of the 1 st level information is Q 1 The storage amount of the 2 nd level information is Q 2 The storage amount of the 3 rd level information is Q 4 And the storage amount of the 4 th level information is Q 4 ：
For Q 1 ～Q 4 For example, there are: q 1 >Q 2 >Q 3 >Q 4 ；
S300, the current key frame is the Yth key frame, and the information of layers 1-4 is extracted from the Yth key frame: x 1，Y 、X 2，Y 、X 3，Y 、X 4，Y ；
And simultaneously calculating the storage importance coefficient of the information of the 1 st to 4 th layers extracted from the Y-th key frame: z 1，Y 、Z 2，Y 、Z 3，Y 、Z 4，Y (ii) a Storing the calculation principle of the importance coefficient;
X 1，Y 、X 2，Y 、X 3，Y 、X 4，Y respectively represent: level 1 information of a Y-th key frame, level 2 information of the Y-th key frame, level 3 information of the Y-th key frame, and level 4 information of the Y-th key frame;
Z 1，Y 、Z 2，Y 、Z 3，Y 、Z 4，Y respectively represent: the storage importance coefficient of the 1 st level information of the Y-th key frame, the storage importance coefficient of the 2 nd level information of the Y-th key frame, the storage importance coefficient of the 3 rd level information of the Y-th key frame and the storage importance coefficient of the 4 th level information of the Y-th key frame;
s400, the storage importance coefficient of the information of the 1 st to 4 th layers extracted from the current Y-th key frame is: z 1，Y 、Z 2，Y 、Z 3，Y 、Z 4，Y Adding the importance coefficient into a storage importance coefficient matrix of the current key frame level information:
all storage importance parameters of the extracted 1 st-4 th-level information of the Y-th key frame are stored into a storage importance coefficient matrix of the current key frame level information;
the above steps are expressed as follows:
Figure FDA0003714538800000041
s500, extracting the information of the 1 st to 4 th layers from the current Y-th key frame: x 1，Y 、X 2，Y 、X 3，Y 、X 4，Y， Adding the key frame into a current key frame level information matrix:
when 0 is present<Y≤Q 4 When the current key frame set is selected, all the level 1-4 information extracted from the Y key frame is stored into the current key frame set;
the above steps are expressed as follows:
Figure FDA0003714538800000042
when Q is j <Y≤Q j-1 When j represents 2 to 4; storing all the level information from level 1 to level j-1 of the Yth key frame into the current key frame set, wherein the steps are expressed by adopting the following formula:
Figure FDA0003714538800000043
for the j-th to 4-th level information of the Y-th key frame, calculation is carried out layer by layer to determine whether to store:
for any of the jth to 4 th layers,
first, from Z β,1 ,Z β,2 ……Z β,I ……Z β,Y-1 Finding the minimum value, which takes Z β,m To indicate that the information storage importance parameter of the beta level of the mth key frame is minimum;
secondly, according to Z β,m 、Z β,Y Determines whether to store the beta level information X of the Y-th key frame β,Y ：
When Z is β,m >Z β,Y
Then Z β,Y Assigning a new value NULL or + ∞sothat Z β,Y No longer participate in the ranking;
X β,Y giving a new value of NULL or 0, namely not storing the beta level information of the Yth key frame;
when Z is β,m ≤Z β,Y
Then Z β,m Given a new value such that Z β,m No longer participate in the ranking;
X β,m assigning a new value of NULL or 0, i.e., deleting the beta level information of the mth key frame and adding the beta level information X of the Yth key frame β,Y Storing, i.e. storing the beta level information of the mth key frameThe storage space is used for storing beta level information of the Y key frame;
when Q is 1 <When Y is in the range of:
for the level 1-4 information of the Y key frame, calculating layer by layer, and determining whether to store:
for any beta-th layer of the 1 st to 4 th layers,
first, from Z β,1 ,Z β,2 ……Z β,I ……Z β,Y-1 Finding the minimum value, which takes Z β,m The information storage importance parameter of the mth key frame beta level is minimum;
secondly, according to Z β,m 、Z β,Y Determines whether to store the beta level information X of the Y-th key frame β,Y ：
When Z is β,m >Z β,Y
Then Z β,Y Assigning a new value NULL or + ∞sothat Z β,Y No longer participate in the ranking;
X β,Y giving a new value of NULL or 0, namely, not storing the beta level information of the Yth key frame;
when Z is β,m ≤Z β,Y
Then Z β,m Given a new value such that Z β,m No longer participate in the ranking;
X β,m assigning a new value of NULL or 0, i.e., deleting the beta level information of the mth key frame and adding the beta level information X of the Yth key frame β,Y And storing, namely, the storage space of the beta level information of the mth key frame is made to be the beta level information storage space of the Yth key frame.
5. The SLAM method as claimed in claim 4 wherein in step S300, the storage importance coefficients for intersections are located at 1.0, the storage importance coefficients for intersections are located at 0.8, and the storage importance coefficients for the middle of the road are located at 0.5.
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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109661659A (en) * 2018-07-19 2019-04-19 驭势科技（北京）有限公司 The storage of vision positioning map and loading method, device, system and storage medium
CN109711365A (en) * 2018-12-29 2019-05-03 佛山科学技术学院 A kind of vision SLAM winding detection method and device merging semantic information
CN109903314A (en) * 2019-03-13 2019-06-18 腾讯科技（深圳）有限公司 A kind of method, the method for model training and the relevant apparatus of image-region positioning
CN110533587A (en) * 2019-07-03 2019-12-03 浙江工业大学 A kind of SLAM method of view-based access control model prior information and map recovery
CN110598713A (en) * 2019-08-06 2019-12-20 厦门大学 Intelligent image automatic description method based on deep neural network
CN112258600A (en) * 2020-10-19 2021-01-22 浙江大学 Simultaneous positioning and map construction method based on vision and laser radar
CN112904901A (en) * 2021-01-14 2021-06-04 吉林大学 Path planning method based on binocular vision slam and fusion algorithm

Family Cites Families (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR100371513B1 (en) * 1999-12-06 2003-02-07 주식회사 팬택앤큐리텔 Method and apparatus of summerizing and browsing video sequences using fidelity values of key frame stored in its edge of key frame hierarchy
US9674507B2 (en) * 2013-04-30 2017-06-06 Qualcomm Incorporated Monocular visual SLAM with general and panorama camera movements
US10533850B2 (en) * 2013-07-12 2020-01-14 Magic Leap, Inc. Method and system for inserting recognized object data into a virtual world
US9355123B2 (en) * 2013-07-19 2016-05-31 Nant Holdings Ip, Llc Fast recognition algorithm processing, systems and methods
US10217221B2 (en) * 2016-09-29 2019-02-26 Intel Corporation Place recognition algorithm
US11187536B2 (en) * 2018-01-12 2021-11-30 The Trustees Of The University Of Pennsylvania Probabilistic data association for simultaneous localization and mapping
CN108830220B (en) * 2018-06-15 2021-01-05 山东大学 Visual semantic library construction and global positioning method based on deep learning
CN109671120A (en) * 2018-11-08 2019-04-23 南京华捷艾米软件科技有限公司 A kind of monocular SLAM initial method and system based on wheel type encoder
CN111461140B (en) * 2020-03-30 2022-07-08 北京航空航天大学 Linear descriptor construction and matching method suitable for SLAM system
CN112240768A (en) * 2020-09-10 2021-01-19 西安电子科技大学 Visual inertial navigation fusion SLAM method based on Runge-Kutta4 improved pre-integration

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109661659A (en) * 2018-07-19 2019-04-19 驭势科技（北京）有限公司 The storage of vision positioning map and loading method, device, system and storage medium
CN109711365A (en) * 2018-12-29 2019-05-03 佛山科学技术学院 A kind of vision SLAM winding detection method and device merging semantic information
CN109903314A (en) * 2019-03-13 2019-06-18 腾讯科技（深圳）有限公司 A kind of method, the method for model training and the relevant apparatus of image-region positioning
CN110533587A (en) * 2019-07-03 2019-12-03 浙江工业大学 A kind of SLAM method of view-based access control model prior information and map recovery
CN110598713A (en) * 2019-08-06 2019-12-20 厦门大学 Intelligent image automatic description method based on deep neural network
CN112258600A (en) * 2020-10-19 2021-01-22 浙江大学 Simultaneous positioning and map construction method based on vision and laser radar
CN112904901A (en) * 2021-01-14 2021-06-04 吉林大学 Path planning method based on binocular vision slam and fusion algorithm

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
Semantic SLAM with Autonomous Object-Level Data Association;Zhentian Qian et.al;《2021 IEEE International Conference on Robotics and Automation (ICRA 2021)》;20210604;第11203-11209页 *
基于视觉SLAM的物体实例识别与语义地图构建;吴皓等;《华中科技大学学报（自然科学版）》;20190930;第47卷(第9期);第47-54页 *

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