JP2023084219A - Position estimation device, autonomous driving vehicle, and position estimation program - Google Patents

Abstract

To appropriately perform position estimation.SOLUTION: An unmanned carrier 1 comprises: a distance sensor 24 mounted on a drivable vehicle body 10 and capable of acquiring two-dimensional distance information around the vehicle body; a storage unit 26 in which a 3D map 261 is preliminarily stored; and a control unit 27. The control unit 27 estimates a position of the vehicle body 10 on the basis of the two-dimensional distance information acquired by the distance sensor 24 and the 3D map 261.SELECTED DRAWING: Figure 4

Description

The present invention relates to a position estimation device, an autonomous vehicle, and a position estimation program.

BACKGROUND ART Conventionally, in a vehicle or the like that automatically operates, the self-position is sequentially estimated while acquiring the surrounding conditions.
For example, in the technique described in Patent Document 1, surrounding point group information is acquired by three-dimensional LiDAR (LASER Imaging Detection and Ranging), and self-location is estimated by comparing this with map data.

JP 2019-109332 A

However, position estimation based on three-dimensional surrounding information enables estimation of six degrees of freedom (three translations and three rotations), but the calculation cost increases accordingly. In addition, three-dimensional measuring instruments such as 3D-LiDAR, which can obtain three-dimensional surrounding information, are more expensive than two-dimensional measuring instruments.

SUMMARY OF THE INVENTION The present invention has been made in view of the above circumstances, and an object of the present invention is to suitably perform position estimation.

A position estimation device according to the present invention includes:
a measuring means mounted on a drivable vehicle body and capable of acquiring two-dimensional distance information around it;
a storage means for pre-storing three-dimensional map information;
estimating means for estimating the position of the vehicle body based on the two-dimensional distance information acquired by the measuring means and the three-dimensional map information;
It was configured to include

An autonomous vehicle according to the present invention includes:
the position estimating device;
the vehicle body;
It was configured to include

A position estimation program according to the present invention comprises:
A computer of a position estimating device mounted on a drivable vehicle body and equipped with a measuring means capable of obtaining two-dimensional distance information around the vehicle and a storage means storing three-dimensional map information in advance,
estimating means for estimating the position of the vehicle body based on the two-dimensional distance information acquired by the measuring means and the three-dimensional map information;
It was assumed to function as

According to the present invention, position estimation can be preferably performed.

It is a figure which shows the working state of the automatic guided vehicle which concerns on embodiment. It is a block diagram showing a schematic control configuration of the automatic guided vehicle according to the embodiment. FIG. 4 is a diagram for explaining a normal map according to the embodiment; FIG. 6 is a flowchart showing the flow of position estimation processing according to the embodiment; It is a figure which shows the route search example using a normal map.

BEST MODE FOR CARRYING OUT THE INVENTION Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

[Configuration of automatic guided vehicle]
FIG. 1 is a diagram showing a working state of an automatic guided vehicle 1 according to this embodiment.
As shown in this figure, the automatic guided vehicle 1 according to the present embodiment is, for example, an automated guided forklift (AGF) that unmannedly conveys a load L in a warehouse, a factory, or the like. ), and perform the prescribed cargo handling work based on the operation commands, etc. The unmanned guided vehicle 1 is an example of an autonomous vehicle according to the present invention, and by mounting the position estimation device according to the present invention, the automatic guided vehicle 1 can suitably estimate its own position in a work area (running area) including an inclined surface S. cargo handling work.

Specifically, the vehicle body 10 of the automatic guided vehicle 1 includes a vehicle body 11 , a fork 12 , an elevating body (lift) 13 , a mast 14 and wheels 15 . The mast 14 is provided in front of the vehicle body 11 and is driven by a drive source (not shown) to tilt forward and backward of the vehicle body 11 . The lifting body 13 is driven by a drive source (not shown) and moves up and down along the mast 14 . A pair of left and right forks 12 for holding a load L, a pallet, and the like are attached to the lifting body 13 . The pair of forks 12 can be tilted and lifted with respect to the vehicle body 11 by driving the mast 14 and the lifting body 13 .

FIG. 2 is a block diagram showing a schematic control configuration of the automatic guided vehicle 1. As shown in FIG.
As shown in this figure, the automatic guided vehicle 1 includes a driving unit 21, a communication unit 23, a distance sensor 24, an inertial measurement unit (IMU) 25, a storage unit 26, and a control unit 27 in addition to the above configuration. Prepare. A position estimation device according to the present invention includes a distance sensor 24 , a storage section 26 and a control section 27 .

The driving unit 21 includes a traveling motor, a steering motor, and a cargo handling motor (all of which are not shown), which are various driving sources of the automatic guided vehicle 1 . The travel motor drives drive wheels of the wheels 15 . The steering motor rotates (steers) the steered wheels of the wheels 15 . The cargo-handling motor is a driving source for raising and lowering the lifting body 13 and tilting the mast 14 .
The communication unit 23 communicates with the management server 40 and the like. Communication by the communication unit 23 may be performed directly with a communication unit such as the management server 40 or may be performed via a communication network.
The management server 40 is a computer that manages the transportation system including the automatic guided vehicle 1, and performs operations such as sending operation commands to the automatic guided vehicle 1 based on user operations and predetermined programs.

The distance sensor 24 can acquire distance information (depth information) of a predetermined two-dimensional area around the vehicle body 10 and outputs the acquired information to the control section 27 . The distance sensor 24 is an example of measuring means according to the present invention, and is a two-dimensional LiDAR (LASER Imaging Detection and Ranging) in this embodiment.
The distance sensor 24 of the present embodiment is installed on the top surface of the vehicle body 11 (see FIG. 1), and measures a predetermined radius area within a plane substantially orthogonal to the vertical direction of the vehicle body 11 . However, the measurement area of the distance sensor 24 may be a planar area.

The inertial measurement device 25 measures the three-dimensional acceleration and angular velocity of the automatic guided vehicle 1 and outputs the results to the controller 27 .

The control unit 27 includes, for example, a CPU (Central Processing Unit), and controls the operation of each unit of the automatic guided vehicle 1 . Specifically, the control unit 27 operates the driving unit 21 based on an operation command received from the management server 40 through the communication unit 23, expands a program stored in advance in the storage unit 26, and expands the expanded program. and execute various processes in cooperation with

The storage unit 26 is a memory configured by RAM (Random Access Memory), ROM (Read Only Memory), etc., stores various programs and data, and also functions as a work area for the control unit 27 .
The storage unit 26 of this embodiment stores a position estimation program 260, a 3D map 261, a normal map 262, and an elevation map 263 in advance.
The position estimation program 260 is a program for executing position estimation processing (see FIG. 4), which will be described later.

The 3D map 261 is three-dimensional point cloud data of the work area in this embodiment. The 3D map 261 is not particularly limited, but is acquired in advance by, for example, measuring the topography with the 3D LiDAR while running the automatic guided vehicle 1 equipped with the 3D LiDAR (distance sensor) in the work area. This 3D mapping is performed each time, for example, the layout of the work area is changed, and the 3D map 261 is updated to the latest one. Note that the 3D map 261 may be three-dimensional map information (terrain information) of an area including at least the work area.

The normal map 262 is inclination information of the work area having normal direction information of the terrain surface (in this embodiment, the road surface on which the automatic guided vehicle 1 travels), and is obtained from the 3D map 261 in advance. Specifically, for example, when there is a terrain as shown in FIG. 3A, first, normal vectors (xyz coordinate values) of each grid are obtained. By converting the xyz values of the acquired normal vector into RGB values, a two-dimensional color map shown in FIG. , the normal map 262 is generated.
The elevation map 263 is the height information of the work area having terrain elevation information, and is obtained from the 3D map 261 in advance.
Note that the normal map 262 and elevation map 263 do not have to be obtained from the 3D map 261 as long as they contain necessary information (inclination information and height information).

[Position estimation process]
Next, the operation of the automatic guided vehicle 1 performing the position estimation process during cargo handling work will be described. FIG. 4 is a flowchart showing the flow of position estimation processing.
The position estimation process is a process in which the automatic guided vehicle 1 estimates its own position during cargo handling work, and is executed by the control unit 27 of the automatic guided vehicle 1 reading out the position estimation program 260 from the storage unit 26 and developing it. be. In cargo handling work, the automated guided vehicle 1 acquires its own position by position estimation processing, and performs various operations (loading, loading, loading, unloading, transportation, etc.).

As shown in FIG. 4, when the position estimation process is executed, the control unit 27 first acquires distance information of a two-dimensional area around the vehicle body 10 using the distance sensor 24 (two-dimensional LiDAR) (step S1).

Next, the control unit 27 collates the obtained two-dimensional distance information with the 3D map 261 (step S2). At this time, the control unit 27 performs matching between the distance information and the 3D map 261 while using the normal map 262 and the elevation map 263 as an auxiliary. In other words, in this matching, the position and posture including the height of the vehicle body 10 are estimated by using the normal map 262 and the elevation map 263, and the obtained two-dimensional distance information is compared with the 3D map 261. . Then, the position on the 3D map 261 that matches well is calculated as the self-position.

As a result, the self-position can be calculated by appropriately considering the posture (inclination) and height position of the vehicle body 10 without using three-dimensional measurement means.
In other words, position estimation using a three-dimensional measuring means can estimate six degrees of freedom (three translations and three rotations), but the calculation cost increases accordingly, and the measuring equipment is relatively expensive. be. On the other hand, position estimation using two-dimensional measurement means uses less expensive measuring instruments and can reduce calculation costs, but the number of degrees of freedom for calculation is limited to three degrees of freedom (two translations and one rotation). difficult to apply to In this regard, in the present embodiment, the posture and height position of the vehicle body 10 can be suitably considered without requiring three-dimensional measurement means.

In step S2, the normal map 262 and the elevation map 263 are used as auxiliaries, but the two-dimensional distance information and the 3D map 261 may be matched without using them. However, it is of course preferable to use at least one of the normal map 262 and the elevation map 263, particularly in terms of reducing the number of calculations. When using either one, it is more preferable to use the normal map 262 .
Further, instead of the normal map 262 and the elevation map 263, other sensors that acquire information on the height and inclination (orientation) of the vehicle body 10 may be used. For example, attitude information may be obtained from the inertial measurement unit 25 .

Next, the control unit 27 determines whether or not to end the position estimation process (step S3), and if it determines not to end it (step S3; No), the process proceeds to the above-described step S1, Self-position estimation (calculation) is continuously and repeatedly executed during cargo handling work.
Then, when it is determined that the position estimation process is to end due to, for example, the end of cargo handling work (step S3; Yes), the control unit 27 ends the position estimation process.

[Technical effect of the present embodiment]
As described above, according to the present embodiment, the position of the vehicle body 10 is estimated based on the two-dimensional distance information acquired by the distance sensor 24 and the 3D map 261 .
As a result, the calculation cost can be reduced compared to position estimation based on three-dimensional distance information. Also, the distance sensor 24 that acquires two-dimensional distance information can be inexpensive compared to a three-dimensional measuring instrument such as 3D-LiDAR. Furthermore, the control unit 27 can also be a low-cost one with lower computing power.
Therefore, position estimation can be performed more favorably than position estimation based on three-dimensional distance information such as 3D-LiDAR.

Further, according to the present embodiment, by using the normal map 262 and the elevation map 263, the posture (inclination) and height position of the vehicle body 10 can be appropriately considered to estimate the self-position. Therefore, the self-position can be preferably estimated even in a work area including elevation differences.

[others]
Although the embodiments of the present invention have been described above, the present invention is not limited to the above embodiments (including modifications).
For example, in the position estimation processing of the above-described embodiment, the normal map 262 may be used to search for a route in consideration of the slope and height of the terrain.
At this time, if there is no anisotropy in the permissible acceleration in the front-rear direction and the width direction of the vehicle body 10, the cost of running on an inclined surface can be incorporated into a route search algorithm such as the A* algorithm. The angle formed by the line and the Z axis can be directly integrated as the cost. Thereby, for example, when the cost of an inclined surface is high, a route avoiding an inclined surface as much as possible is obtained. Alternatively, for example, as shown in FIG. 5A, a route for traveling on an inclined surface within the allowable inclination range of the vehicle body 10 is obtained.
In addition, when the allowable acceleration in the longitudinal direction and the width direction of the vehicle body 10 is anisotropic, by incorporating the normal map 262 into the hybridA* algorithm, the relationship between the ellipse with the normal as the axis and the gravity vector , the cost due to posture should be integrated. As a result, for example, as shown in FIG. 5(b), a route for running on an inclined surface in the longitudinal direction of the vehicle body 10 can be obtained as a low-cost posture.

Moreover, in the above embodiment, the case where the position estimation device is mounted on the automatic guided vehicle is exemplified. However, the target of mounting the position estimation device according to the present invention is not limited to an unmanned guided vehicle as long as it is a mobile body that estimates its own position. etc. It may also be a manned aircraft on which a driver boards. The place of use is not limited to warehouses, factories, and construction sites, but can be widely applied to places (terrain) with undulations (differences in height) such as slopes.
Furthermore, the position estimating device (position estimating program) according to the present invention does not have to be installed in the mobile object, and may be installed in control means (for example, the management server 40) capable of communicating with the mobile object.

Further, in the above embodiment, an automatic guided vehicle is illustrated as an example of an autonomous vehicle according to the present invention. may not be provided.
In addition, the details shown in the above embodiments can be changed as appropriate without departing from the scope of the invention.

1 Automated Guided Vehicles (Autonomous Driving Vehicles)
10 vehicle body 24 distance sensor (measurement means)
25 inertial measurement device 26 storage unit (storage means)
27 control unit (estimation means)
260 position estimation program 261 3D map (three-dimensional map information)
262 normal map (tilt information)
263 elevation map (height information)
S Inclined surface

Claims (7)

a measuring means mounted on a drivable vehicle body and capable of acquiring two-dimensional distance information around it;
a storage means for pre-storing three-dimensional map information;
estimating means for estimating the position of the vehicle body based on the two-dimensional distance information acquired by the measuring means and the three-dimensional map information;
A position estimation device comprising: The storage means pre-stores terrain inclination information,
The estimating means estimates the position of the vehicle body based on the two-dimensional distance information and the three-dimensional map information while using the tilt information as a supplement.
The position estimation device according to claim 1. The storage means pre-stores terrain height information,
The estimation means estimates the position of the vehicle body based on the two-dimensional distance information and the three-dimensional map information while using the height information as a supplement.
The position estimation device according to claim 1 or 2. The measurement means is a two-dimensional LiDAR,
The position estimation device according to any one of claims 1 to 3. the three-dimensional map information includes point cloud data;
The position estimation device according to any one of claims 1 to 4. A position estimation device according to any one of claims 1 to 5;
the vehicle body;
autonomous vehicle. A computer of a position estimating device mounted on a drivable vehicle body and equipped with a measuring means capable of obtaining two-dimensional distance information around the vehicle and a storage means storing three-dimensional map information in advance,
estimating means for estimating the position of the vehicle body based on the two-dimensional distance information acquired by the measuring means and the three-dimensional map information;
A position estimation program that functions as a

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