WO2022219875A1

WO2022219875A1 - Information processing system, information processing device, and information processing method

Info

Publication number: WO2022219875A1
Application number: PCT/JP2022/002935
Authority: WO
Inventors: 啓輔前田; 幹夫中井; 佑允高橋
Original assignee: ソニーグループ株式会社
Priority date: 2021-04-15
Filing date: 2022-01-26
Publication date: 2022-10-20
Also published as: JP2022163931A

Abstract

An information processing system according to one embodiment of the present disclosure comprises a map generating unit, and a setting unit that sets, in accordance with estimated environmental characteristics, a data format for map data generated by the map generating unit.

Description

Information processing system, information processing device, and information processing method

The present disclosure relates to an information processing system, an information processing device, and an information processing method.

In recent years, technologies related to mobile objects such as robots that recognize the external environment and move autonomously according to the recognized environment have been disclosed (see Patent Document 1, for example).

JP 2016-149090 A

A mobile body is equipped with various sensors to recognize the external environment, and an environmental map corresponding to the external environment is constructed based on the sensor data obtained from the various sensors. Real-time processing of environmental maps is required for autonomous mobile objects. Therefore, it is desirable to provide an information processing system, an information processing apparatus, and an information processing method that can reduce the amount of data of an environment map.

An information processing system according to an embodiment of the present disclosure includes a map generation unit and a setting unit that sets the data format of map data generated by the map generation unit according to estimated environmental characteristics.

An information processing apparatus according to an embodiment of the present disclosure includes a setting unit that sets the data format of map data generated by the map generation unit according to estimated environmental characteristics.

An information processing method according to an embodiment of the present disclosure includes setting a data format of map data generated by a map generation unit according to estimated environmental characteristics.

In the information processing system, information processing apparatus, and information processing method according to the embodiment of the present disclosure, the data format of the map data generated by the map generation unit is set according to the estimated environmental characteristics. As a result, for example, even when using an environment map that is compatible with the external environment, it is possible to select an environment map according to the environmental characteristics.

1 is a diagram illustrating an example of functional blocks of an information processing system according to an embodiment of the present disclosure; FIG. It is a figure showing the example which switches map data alternatively. FIG. 10 is a diagram showing an example of temporarily using a plurality of map data when switching map data; FIG. 4 is a diagram summarizing compatibility between map data formats and aircraft types; FIG. 3 is a diagram summarizing compatibility between a map data format and an operation location; 2 is a diagram showing an example of a procedure for selecting a format of map data in the information processing system of FIG. 1; FIG. FIG. 3 is a diagram showing a modified example of the functional blocks of the information processing system of FIG. 1; FIG. 1 and FIG. 5 are diagrams showing a modified example of the schematic configuration of the parameter generator.

EMBODIMENT OF THE INVENTION Hereinafter, the form for implementing this disclosure is demonstrated in detail with reference to drawings. The description will be given in the following order.

1. Embodiment (Figs. 1 to 6)
2. Modified example (Fig. 7, Fig. 8)

<1. Embodiment>
[Constitution]
An information processing system 1 according to an embodiment of the present disclosure will be described. FIG. 1 shows an example of functional blocks of an information processing system 1. As shown in FIG. The information processing system 1 includes, for example, a sensor device section 10, a parameter generation section 20, a storage section 30, an action planning section 40, a control section 50, and an actuator 60, as shown in FIG.

The sensor device unit 10 has, for example, a sensor element 11 that recognizes the external environment and acquires environmental data 11A corresponding to the recognized external environment. The sensor element 11 outputs the acquired environmental data 11A to the parameter generator 20 . The sensor element 11 is, for example, an RGB camera, an RGB-D camera, a depth sensor, an infrared sensor, an event camera, or a sound collection sensor.

The RGB camera is, for example, a single visible light image sensor that outputs RGB image data obtained by receiving visible light and converting it into an electrical signal. The RGB-D camera is, for example, a binocular visible light image sensor, and outputs RGB-D image data (RGB image data and distance image data obtained from parallax). The depth sensor is, for example, a ToF (Time of Flight) sensor or a Lider (Laser Imaging Detection and Ranging), and outputs range image data obtained by measuring scattered light from pulsed laser irradiation. The infrared sensor outputs infrared image data obtained by, for example, receiving infrared rays and converting them into electric signals. The event camera is, for example, a single visible light image sensor, and outputs a difference between RGB image data (difference image data) between frames. The sound collection sensor outputs, for example, sound data obtained from the external environment. The sensor device unit 10 outputs, for example, various data (eg, RGB image data, RGB-D image data, distance image data, infrared image data, differential image data, or audio data) obtained from the external environment as environment data 11A. do.

The parameter generating unit 20 has an environmental characteristic estimating unit 21 , a map selecting unit 22 , a plurality of

map generating units

23 and 24 and a map IF providing unit 25 .

The environmental characteristic estimation unit 21 estimates the environmental characteristic 21A based on the environmental data 11A obtained from the sensor device unit 10. The environmental characteristic 21A is an estimated value of the environmental characteristic generated based on the environmental data 11A, and includes, for example, any one of shape feature amount, image feature amount, and sound feature amount. The shape feature amount indicates, for example, the flatness, the dispersion of the point group, or the average height of the point group in the environment data 11A. The image feature amount indicates, for example, the number of edges, the number of feature points, or the average or variance of hue, brightness, and saturation in the environmental data 11A. The audio feature amount indicates volume, for example.

The map selection unit 22 sets the data format of the map data generated by the

map generation units

23 and 24 according to the estimated environmental characteristics 21A. The map selection unit 22 selects at least one of the

map generation units

23 and 24 as the map generation unit to be used, for example, according to the estimated environmental characteristics 21A. For example, the map selection unit 22 instructs the selected map generation unit to generate a map. The map selection unit 22, for example, provides an array of identifiers ID (identification) of the map generation units to be used, or an array indicating the use of the plurality of

map generation units

23 and 24, to the plurality of

map generation units

23 and 24. may be output. For example, the map selection unit 22 may output a command to instruct map generation or a command to end map generation only to the map generation unit to be used.

The map generation unit 23 uses the environment data 11A to construct the first map data 23A in the first data format. The map generation unit 23 generates the environment map 31 at the current time by superimposing the constructed first map data 23A on the environment map 31 read from the storage unit 30 . The map generation unit 23 stores the generated environment map 31 at the current time in the storage unit 30 . When selected by the map selection unit 22 , the map generation unit 23 outputs all or part of the generated environment map 31 at the current time to the map IF provision unit 25 .

The map generation unit 24 uses the environment data 11A to construct second map data 24A in a second data format different from the first data format. The map generation unit 24 generates the environment map 32 at the current time by superimposing the constructed second map data 24A on the environment map 32 read from the storage unit 30 . The map generation unit 24 stores the generated environment map 32 at the current time in the storage unit 30 . When selected by the map selection unit 22 , the map generation unit 24 outputs all or part of the generated environment map 32 at the current time to the map IF provision unit 25 .

Note that the map generating unit 23 may output the first map data 23A to the map IF providing unit 25 when selected by the map selecting unit 22 . Further, the map generating unit 24 may output the second map data 24A to the map IF providing unit 25 when selected by the map selecting unit 22 . In these cases, the storage unit 30 may be omitted.

The map generation unit 23 may delete past map data that has passed a certain period of time from the environment map 31 . In addition, the map generation unit 24 may delete past map data after a certain period of time has passed from the environment map 32 .

2 and 3, the data format of the first map data 23A used in the map generator 23 is "map data format A", and the data format of the second map data 24A used in the map generator 24 is " It conceptually shows the switching of the map data when the map data format is "B". In FIGS. 2 and 3, arrows show how a moving body equipped with the sensor device unit 10 moves from an area suitable for "map data format A" to an area suitable for "map data format B." .

For example, when selecting the map generation unit 23, the map selection unit 22 switches from the map generation unit 23 to the map generation unit 24 according to the estimated environmental characteristics 21A. At this time, the map selection unit 22 may immediately switch the data format of the map data from "map data format A" to "map data format B", for example, as shown in FIG. For example, as shown in FIG. 3, when switching from "map data format A" to "map data format B", the map selection unit 22 selects "map data format A" and "map data format B" simultaneously. The data format of the map data may be switched from "map data format A" to "map data format B" after a period of use.

The map IF providing unit 25 uses the environmental map (hereinafter referred to as "environmental map 25A") input from at least one of the

map generating units

23 and 24 to generate parameters 25B used in the action plan. The map IF providing unit 25, for example, uses the environment map 25A and the information about the self-position and self-velocity to derive an information map regarding the presence or absence of a collision or the probability of collision, and uses the derived information map as a parameter 25B to create an action plan. You may output to the part 40. FIG.

The map IF providing unit 25 uses, for example, the environment map 25A and information about a certain spatial area (for example, a predetermined spatial area including the self-position) to derive an information map about the obstacle density, and derives the information map. The resulting information map may be output to the action planning section 40 as the parameter 25B. The map IF providing unit 25, for example, generates an obstacle density gradient based on the generated information map about the obstacle density, and outputs information about the generated obstacle density gradient to the action planning unit 40 as a parameter 25B. may The map IF providing unit 25 generates information about the distance from a certain position to obstacles in its surroundings and the direction of obstacles from a certain position, for example, based on the generated information map about the density of obstacles. , the generated information may be output to the action planning unit 40 as the parameter 25B.

The storage unit 30 is a database containing environment maps 31 and 32, for example. The storage unit 30 is configured by, for example, a volatile memory such as a DRAM (Dynamic Random Access Memory), or a nonvolatile memory such as an EEPROM (Electrically Erasable Programmable Read-Only Memory) or flash memory.

The action planning unit 40 creates an action plan based on the parameters 25B input from the map IF providing unit 25. For example, based on the parameter 25B, the action planning unit 40 determines what route, direction, and posture to move from the self position to the target position, and controls the result of the determination as the action plan 40A. Output to unit 50 . The control unit 50 generates a drive signal 50A for driving the actuator 60 based on the action plan 40A input from the action planning unit 40 and outputs the drive signal 50A to the actuator 60 . The actuator 60 drives, for example, a motor of a moving body based on the drive signal 50A input from the control section 50 .

The action plan unit 40 may output the generated action plan 40A to the map IF provision unit 25. In this case, the map IF providing unit 25, for example, uses the environment map 25A and the acquired action plan 40A to derive an information map about the density of obstacles on the route from the current position to the target position, and the derived information The map may be output to the action planning section 40 as the parameter 25B. Below, "the route from the current position to the target position" is referred to as a route RT. For example, the map IF providing unit 25 generates an obstacle density gradient based on the information map about the obstacle density generated in this way, and uses the generated information about the obstacle density gradient as a parameter 25B for the action planning unit 40 may be output. The map IF providing unit 25 generates, for example, information about the distance to the obstacle on the route RT and the direction of the obstacle from the route RT based on the generated information map about the density of obstacles. The information may be output to the action planner 40 as parameters 25B.

Next, the data format of the map data used in the

map generators

23 and 24 will be described with reference to FIGS. 4 and 5. FIG. FIG. 4 is a diagram summarizing the compatibility between the map data format and the aircraft type. FIG. 5 is a diagram summarizing compatibility between the map data format and the operating location. Examples of the data format of the map data used by the

map generators

23 and 24 include the data formats listed below.
1. grid map
2. voxel map
3. Octo Map
4. Height map
5. Hilbert Map
6. Multiplanar Map
7. Polygon Map

　Grid Map is a map data format that expresses the presence or absence of obstacles as a two-dimensional image. This is suitable when the moving body moves two-dimensionally. In Grid Map, the amount of data is small when the road surface is less uneven. Therefore, the Grid Map is suitable for small vehicles with a small amount of data, and is not very suitable for self-driving vehicles due to the large amount of calculation. Grid Map does not support three-dimensional space, so it cannot be applied to drones, multi-legged robots, and manipulators that handle three-dimensional space. In addition, Grid Map is suitable for home environments, factories, and hospitals where the floors are less uneven. However, it is not suitable for roads because the road surface is uneven and the amount of calculation is large. In addition, since Grid Map does not support unevenness, it is not very suitable for forests and tunnels, and cannot be applied to hills, unevenness, and object manipulation that handle three-dimensional space.

　Voxel Map is a map data format that expresses space as a collection of three-dimensional rectangular parallelepipeds. The two horizontal axes can have the same resolution, while the vertical resolution can be set to be different from the two horizontal axes. Further, it is possible to set limits on the range of values. Voxel Map can express any shape, but the amount of data is large. Therefore, Voxel Map is not very suitable for small vehicles, multi-legged robots, and manipulators due to the large amount of calculation, and cannot be applied to self-driving cars and drones due to the enormous amount of calculation. In addition, Voxel Map is suitable for a home environment with a small amount of data, and is not so suitable for factories/hospitals, hills/unevenness, forests/tunnels, and object manipulation in that the amount of calculation is large, and the amount of calculation is enormous. Therefore, it cannot be applied to roads.

Octo Map is a map data format that uses a tree structure called Octree. Good compatibility with man-made objects such as buildings. If the environment is a set of rectangular parallelepipeds, or if the Cartesian coordinate system for creating the map matches the planar direction of the environment, the amount of data will be small. Therefore, OctoMap is suitable for small vehicles, drones, multi-legged robots, and manipulators, where the amount of data is small. Octo Map is suitable for home environments, factories/hospitals, hills/unevenness, forests/tunnels, and object manipulation where the amount of data is small. .

Height Map is a map data format that expresses altitude information as a two-dimensional image. Good compatibility with uneven road surfaces. When representing an uneven road surface, the amount of data is smaller than that of Voxel Map and Octo Map. However, when the road surface is a horizontal plane, the amount of data is larger than that of Voxel Map and Octo Map. In addition, when there is something flying in the air, it cannot be expressed appropriately. Therefore, Height Map is suitable for small vehicles, self-driving cars, and multi-legged robots with small amount of data, but it may not be suitable for drones depending on the environment, and it cannot represent objects for manipulators. Not applicable. In addition, Height Map is suitable for roads, hills, and irregularities, but it cannot be applied to home environments, factories, hospitals, forests, and tunnels because it cannot represent the bottom of objects. Also not applicable to operations.

Hilbert Map is a map data format that expresses shapes as a set of three-dimensional Gaussian distributions (elliptical spheres). Good compatibility with natural objects. Arbitrary shapes can be approximated and represented, and when the environment is composed of various shapes and angles, the amount of data is smaller than Voxel Map and Octo Map. Therefore, Hilbert Map is suitable for small vehicles, drones, and multi-legged robots because the amount of data is small, but it is not so suitable for self-driving cars because the amount of calculation is large. It is not applicable to manipulators in that it is inferior. In addition, Hilbert Map is suitable for home environments, hills/unevenness, forests/tunnels in that the amount of data is small. However, it is not very suitable for factories, hospitals, and object manipulation because of its poor shape accuracy, and it is not very suitable for roads because of its large amount of calculations.

　MultiPlanar Map is a map data format that expresses shapes as a collection of multiple planes. It works well indoors, especially in buildings with little unevenness. If the environment consists of a set of planar shapes, the amount of data will be small. Therefore, the MultiPlanar Map is suitable for small vehicles in that the amount of data is small. However, its poor shape accuracy makes it unsuitable for self-driving cars and drones, and its extremely poor shape accuracy makes it unsuitable for manipulators. is also not applicable. In addition, MultiPlanar Map is suitable for factories and hospitals in that the amount of data is small, but it is not so suitable for home environments and roads in terms of shape accuracy. Not applicable to unevenness, forest/tunnel, and object manipulation.

Polygon Map is a map data format that expresses shapes as a set of multiple convex polyhedrons (including a set of prisms and cylinders). It is compatible with the road environment of self-driving cars. When the environment is such that structures are lined up on the road surface, the amount of data becomes small. Therefore, Polygon Map is suitable for small vehicles and self-driving cars in that the amount of data is small, but it is not so suitable for drones and manipulators where it is difficult to divide the environment into multiple convex polyhedra. It cannot be applied to manipulators because the shape accuracy is significantly inferior. Also, Polygon Map is suitable for factories, hospitals, and roads in that the amount of data is small. However, it is not very suitable for home environments, forests, or tunnels, where it is difficult to divide the environment into multiple convex polyhedrons. It cannot be applied to hills and irregularities that are extremely difficult to divide into polyhedrons.

[motion]
Next, selection of the map data format in the information processing system 1 will be described.

FIG. 6 shows an example of the map data format selection procedure in the information processing system 1 . The map selection unit 22 first searches for planes included in the environmental characteristics 21A (step S101). When a plane is detected in the environmental characteristics 21A (step S102; Y), the map selection unit 22 clusters points above the detected plane in the environmental characteristics 21A (step S103). As a result, when a large number of objects that can be planarly approximated exist (step S104; Y), the map selection unit 22 selects MultiPlanar Map (step S105).

On the other hand, if the number of objects that can be planarly approximated is small (step S104; N), the map selection unit 22 determines whether there are many convex objects. As a result, when a large number of convex objects exist (step S106; Y), the map selection unit 22 selects Polygon Map (step S107). If the number of convex objects is small (step S106; N), the map selection unit 22 selects Grid Map (step S108).

When a plane is not detected in the environmental characteristics 21A (step S102; N), the map selection unit 22 creates a height histogram using the environmental characteristics 21A (step S109). At this time, when the histogram has one peak (step S110; Y), the map selection unit 22 selects Height Map (step S111). On the other hand, if the histogram has a plurality of peaks (step S110; N), the map selection unit 22 selects Octo Map or Hilbert Map (step S112).

[effect]
Next, effects of the information processing system 1 will be described.

In the present embodiment, the data format of the map data generated by the map generation unit 23 is set according to the environmental characteristics 21A estimated by the environmental characteristics estimation unit 21. As a result, for example, even when using an environment map that is compatible with the external environment, it is possible to select an environment map according to the environmental characteristics. As a result, the data amount of the environment map can be kept low, so the environment map can be processed in real time, and the moving object can be moved autonomously.

Also, in the present embodiment, any one of the shape feature amount, the image feature amount, and the sound feature amount is used as the environmental characteristic 21A. As a result, it is possible to select the data format of the map data suitable for the environment. As a result, the data amount of the environment map can be kept low, so the environment map can be processed in real time, and the moving object can be moved autonomously.

Also, in the present embodiment, the environmental characteristics 21A are estimated based on the environmental data 11A acquired by the sensor device unit 10. As a result, even if the moving object equipped with the sensor device unit 10 moves from an area suitable for "map data format A" to an area suitable for "map data format B", for example, The data format of map data can be selected in real time. Since the data volume of the environment map can be kept low in real time, the environment map can be processed in real time, and the moving body can be moved autonomously.

Also, in the present embodiment, map generation is instructed to at least one of the map generation unit 23 and the map generation unit 24 according to the environmental characteristics 21A. As a result, for example, even when using an environment map that is compatible with the external environment, it is possible to select an environment map according to the environmental characteristics. As a result, the data amount of the environment map can be kept low, so the environment map can be processed in real time, and the moving object can be moved autonomously.

In addition, in the present embodiment, the map data generated by the map generation unit 23 is used to generate the parameters 25B used for the action plan. As a result, for example, it is possible to accurately determine what path, direction, and posture to move from the self position to the target position. Therefore, it is possible to accurately generate an action plan.

Also, in the present embodiment, an action plan is created using the generated parameters 25B. This makes it possible to accurately generate an action plan. Further, in the present embodiment, the map data generated by the map generating section 23 and the action plan created by the action planning section 40 are used to generate the parameter 25B. As a result, not only the current position but also the route from the current position to the target position can be judged where there is a risk of collision with an obstacle, and the route can be reconstructed to avoid obstacles. becomes.

<2. Variation>
[Modification A]
In the above embodiments and modifications thereof, the sensor device section 10 may have the signal processing section 12 as shown in FIG. 7, for example. The signal processing unit 12 processes environmental data 11A output from the sensor element 11 . The signal processing unit 12 detects, for example, an ROI included in the environment data 11A, and outputs data of the location corresponding to the detected ROI in the environment data 11A to the parameter generation unit 20 as the environment data 12A. By reducing the amount of data in advance in the sensor device unit 10 in this manner, the environment map can be processed in real time, and the moving object can be moved autonomously.

[Modification B]
In the above embodiments and their modifications, various functions included in the parameter generator 20 may be realized by hardware or by software. In the above embodiments and modifications thereof, the parameter generation unit 20 may be configured by, for example, a calculation unit 26 and a storage unit 27 as shown in FIG. In this case, the storage unit 27 stores a parameter generation program 27a that implements various functions included in the parameter generation unit 20 . The computing unit 26 includes, for example, a CPU (Central Processing Unit) and a GPU (Graphics Processing Unit). By loading the parameter generation program 27 a into the calculation unit 26 , the calculation unit 26 can execute various functions included in the parameter generation unit 20 .

Although the present disclosure has been described above with reference to the embodiment and modifications thereof, the present disclosure is not limited to the above-described embodiment and the like, and various modifications are possible. For example, in the above-described embodiments and the like, the sensor device section 10, the parameter generation section 20, the storage section 30, the action planning section 40, the control section 50 and the actuator 60 may all be mounted on a moving body. Further, for example, in the above embodiments and the like, the sensor device unit 10, the control unit 50, and the actuator 60 are mounted on the moving object, and the other configurations (for example, the parameter generation unit 20, the storage unit 30, the action planning unit 40). may be provided in a server device configured to be able to communicate with a mobile unit.

It should be noted that the effects described in this specification are merely examples. The effects of the present disclosure are not limited to the effects described herein. The disclosure may have advantages other than those described herein.

Further, for example, the present disclosure can have the following configuration.
(1)
a map generator;
An information processing system comprising: a setting unit that sets a data format of map data generated by the map generation unit according to the estimated environmental characteristics.
(2)
(1) The information processing system according to (1), wherein the environmental characteristics include any one of a shape feature amount, an image feature amount, and an audio feature amount.
(3)
a sensor unit that acquires environmental data;
The information processing system according to (1) or (2), further comprising: an estimation unit that estimates the environmental characteristics based on the environmental data acquired by the sensor unit.
(4)
The map generation unit
a first map generator that generates first map data in a first data format;
a second map generator that generates second map data in a second data format different from the first data format,
According to any one of (1) to (3), the setting unit instructs at least one of the first map generation unit and the second map generation unit to generate a map according to the environmental characteristics. information processing system.
(5)
The information processing system according to any one of (1) to (4), further comprising a parameter generator that generates parameters used for an action plan using the map data generated by the map generator.
(6)
(5) The information processing system according to (5), further comprising an action planning unit that creates the action plan using the parameters generated by the parameter generation unit.
(7)
The information processing system according to (6), wherein the parameter generating section generates the parameters using the map data generated by the map generating section and the action plan created by the action planning section.
(8)
An information processing apparatus comprising a setting unit for setting a data format of map data generated by a map generation unit according to estimated environmental characteristics.
(9)
An information processing method including setting a data format of map data generated by a map generation unit according to the estimated environmental characteristics.

In the information processing system, information processing apparatus, and information processing method according to the embodiment of the present disclosure, the data format of the map data generated by the map generation unit is set according to the estimated environmental characteristics. As a result, for example, even when using an environment map that is compatible with the external environment, it is possible to select an environment map according to the environmental characteristics. As a result, it is possible to keep the data amount of the environment map low even when the mobile body moves across external environments having different environmental characteristics.

This application claims priority based on Japanese Patent Application No. 2021-069082 filed on April 15, 2021 at the Japan Patent Office, and the entire contents of this application are incorporated herein by reference. incorporated into the application.

Depending on design requirements and other factors, those skilled in the art may conceive various modifications, combinations, subcombinations, and modifications that fall within the scope of the appended claims and their equivalents. It is understood that

Claims

a map generator;
An information processing system comprising: a setting unit that sets a data format of map data generated by the map generation unit according to the estimated environmental characteristics.
The information processing system according to claim 1, wherein the environmental characteristics include any one of a shape feature amount, an image feature amount, and an audio feature amount.
a sensor unit that acquires environmental data;
The information processing system according to claim 1, further comprising an estimation unit that estimates the environmental characteristics based on the environmental data acquired by the sensor unit.
The map generation unit
a first map generator that generates first map data in a first data format;
a second map generator that generates second map data in a second data format different from the first data format,
The information processing system according to claim 1, wherein the setting unit instructs at least one of the first map generation unit and the second map generation unit to generate a map according to the environmental characteristics.
The information processing system according to claim 1, further comprising a parameter generator that generates parameters used for an action plan using the map data generated by the map generator.
The information processing system according to claim 5, further comprising an action planning section that creates the action plan using the parameters generated by the parameter generation section.
The information processing system according to claim 6, wherein the parameter generating section generates the parameters using the map data generated by the map generating section and the action plan created by the action planning section.
An information processing apparatus comprising a setting unit for setting a data format of map data generated by a map generation unit according to estimated environmental characteristics.
An information processing method including setting a data format of map data generated by a map generation unit according to the estimated environmental characteristics.