CN113741473A - Photocatalyst mobile robot and map construction method - Google Patents
Photocatalyst mobile robot and map construction method Download PDFInfo
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- CN113741473A CN113741473A CN202111066245.0A CN202111066245A CN113741473A CN 113741473 A CN113741473 A CN 113741473A CN 202111066245 A CN202111066245 A CN 202111066245A CN 113741473 A CN113741473 A CN 113741473A
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- 239000011941 photocatalyst Substances 0.000 title claims abstract description 19
- 238000010276 construction Methods 0.000 title claims abstract description 7
- 238000004891 communication Methods 0.000 claims abstract description 8
- 230000001133 acceleration Effects 0.000 claims description 10
- 238000006073 displacement reaction Methods 0.000 claims description 10
- 238000000746 purification Methods 0.000 claims description 10
- 238000000034 method Methods 0.000 claims description 7
- 238000001514 detection method Methods 0.000 claims description 6
- 238000004887 air purification Methods 0.000 abstract description 8
- 238000011161 development Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008094 contradictory effect Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0234—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons
- G05D1/0236—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using optical markers or beacons in combination with a laser
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0223—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving speed control of the vehicle
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0238—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors
- G05D1/024—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using obstacle or wall sensors in combination with a laser
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
- G05D1/0246—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means
- G05D1/0251—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using a video camera in combination with image processing means extracting 3D information from a plurality of images taken from different locations, e.g. stereo vision
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0276—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle
- G05D1/0285—Control of position or course in two dimensions specially adapted to land vehicles using signals provided by a source external to the vehicle using signals transmitted via a public communication network, e.g. GSM network
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Remote Sensing (AREA)
- Radar, Positioning & Navigation (AREA)
- Aviation & Aerospace Engineering (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Electromagnetism (AREA)
- Optics & Photonics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Multimedia (AREA)
- Acoustics & Sound (AREA)
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention provides a photocatalyst mobile robot, which comprises a shell, a wireless communication module, a mobile assembly, a sensor module, a filter and an ROS module, wherein the shell is provided with a plurality of Light Emitting Diodes (LEDs); the sensor module comprises a depth-of-field camera and a laser radar, wherein the depth-of-field camera and the laser radar are arranged on the shell, the depth-of-field camera is used for acquiring a local three-dimensional cloud picture, and the laser radar is used for acquiring the distance between a local characteristic point and the robot; the map construction method comprises the steps of fusing a first grid map generated based on a laser radar and a second grid map generated based on a depth camera to generate an indoor map; information is acquired through the depth-of-field camera and the laser radar, and the ROS module generates an indoor map by using the acquired information, so that the robot moves to a target position according to an instruction of external terminal equipment, and the purifying assembly is driven to automatically purify air; the mobile robot improves the efficiency of air purification and enlarges the range of air purification.
Description
Technical Field
The invention relates to the technical field of robots, in particular to a photocatalyst mobile robot and a map construction method.
Background
In the modern times, the demand of air purification is increasingly expanding in daily life and production process of people, and under the background of the market demand, a photocatalyst air purifier is derived. However, in the society with rapid development of informatization, intelligent, autonomous and convenient internet of things equipment also becomes a main development direction at present. The existing photocatalyst air purification product can not move autonomously, and can automatically purify air in a target area, and the purified area is limited.
Disclosure of Invention
The invention aims to provide a photocatalyst mobile robot and a map construction method, which are used for solving the problem that the purification range of an air purification product in the prior art is limited.
One aspect of the present embodiment provides a photocatalyst mobile robot, including:
a housing: comprises a shell and a chassis arranged at one end of the shell;
the wireless communication module is arranged in the shell and is used for being in wireless connection with an external terminal;
a moving assembly mounted on the chassis; for moving the robot;
the purification assembly comprises an air inlet and an air outlet which are arranged on the surface of the shell; and an air purifier mounted within the housing;
the sensor module comprises a depth-of-field camera and a laser radar, wherein the depth-of-field camera and the laser radar are arranged on the shell, the depth-of-field camera is used for acquiring a local three-dimensional cloud picture, and the laser radar is used for acquiring the distance between a local characteristic point and the robot;
the filter is arranged in the shell and used for acquiring the real-time position and the attitude of the local characteristic point relative to the robot according to the motion state of the robot; the motion state of the robot comprises the acceleration, the angular velocity and the displacement of the robot in the current state;
and the ROS module is arranged in the shell and used for constructing an indoor map according to the local three-dimensional cloud picture and the distance between the local characteristic point and the robot.
Preferably, the sensor module further comprises an ultrasonic module and a cliff sensor, wherein the ultrasonic module is used for detecting an obstacle in front of the robot, and the cliff sensor is used for detecting the height difference of the working platform.
Preferably, the ultrasonic module comprises 3 ultrasonic detectors, and the ultrasonic detectors are arranged on the shell.
Preferably, the moving assembly comprises two driving wheels, a hub motor arranged in the driving wheels, and four auxiliary universal wheels arranged around the chassis.
In a second aspect, the present embodiment provides a map building method based on the above-mentioned photocatalyst mobile robot, the map building method includes,
acquiring displacement, acceleration and speed of the robot;
obtaining the distance and the angle between the local characteristic point and the robot through a laser radar;
acquiring the real-time position and posture of the local characteristic point relative to the robot according to the displacement, the acceleration and the speed of the robot and the distance and the angle between the local characteristic point and the robot so as to generate a first grid map; the local feature points represent a plurality of landmarks within a detection range of the lidar;
acquiring a local image through a depth-of-field camera to generate a local three-dimensional cloud image;
projecting the local three-dimensional cloud image to form a second grid image;
and fusing the first grid map and the second grid map to generate an indoor map.
The first grid graph and the second grid graph are both composed of a plurality of grids, and the state of each grid is occupied or empty;
if the states of the grids of the first grid map and the second grid map are both empty, determining that the state of the grid is empty; and judging the other situations as occupation.
According to the photocatalyst mobile robot, the depth of field camera and the laser radar are used for collecting information, and the ROS module is used for generating an indoor map by using the collected information, so that the robot moves to a target position according to an instruction of external terminal equipment, and drives the purification assembly to automatically purify air; the mobile robot improves the efficiency of air purification and enlarges the range of air purification.
Drawings
Fig. 1 is a schematic structural diagram of a photocatalyst mobile robot according to an embodiment of the present invention;
fig. 2 is a system framework diagram of a photocatalyst mobile robot according to an embodiment of the present invention;
fig. 3 is a flowchart of a map construction method according to a second embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that all the directional indications (such as up, down, left, right, front, back, inner and outer, center … …) in the embodiment of the present invention are only used to explain the relative position relationship between the components, the motion situation, etc. in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indication is changed accordingly.
In the present invention, unless otherwise expressly stated or limited, the terms "connected," "secured," and the like are to be construed broadly, and for example, "secured" may be a fixed connection, a removable connection, or an integral part; can be mechanically or electrically connected; they may be directly connected or indirectly connected through intervening media, or they may be connected internally or in any other suitable relationship, unless expressly stated otherwise. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In addition, the technical solutions in the embodiments of the present invention may be combined with each other, but it must be based on the realization of those skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination of technical solutions should not be considered to exist, and is not within the protection scope of the present invention. .
The following examples are now provided:
the first embodiment is as follows:
as shown in fig. 1 to 2, a photocatalyst mobile robot includes:
a housing 1: comprises a shell 11 and a chassis 12 arranged at one end of the shell 11;
the wireless communication module 2 is arranged in the shell 1 and is used for being wirelessly connected with an external terminal; the wireless terminal such as a web service platform and a mobile phone APP sends instructions through the mobile phone and the web service platform and transmits the instructions to the wireless communication module; the wireless communication module may be a Global System for Mobile communications (GSM), Wideband Code Division Multiple Access (WCDMA), 4G network, 5G network, Bluetooth (Bluetooth), Wi-Fi, or other wireless network module.
The moving assembly 3 is arranged on the chassis; for moving the robot; the moving assembly comprises two driving wheels, a hub motor arranged in the driving wheels and four auxiliary universal wheels arranged around the chassis; the hub motor is a motor which integrates a power system, a transmission system and a brake system of the vehicle.
The purification assembly 4 comprises an air inlet 41 and an air outlet 42 which are arranged on the surface of the shell; and an air purifier (not shown) mounted within the housing; after the air purifier is opened, air is supplied through the air inlet 41 and is discharged through the air outlet 42, so that air circulation is realized.
The sensor module 5 comprises a depth-of-field camera 51 and a laser radar 52, which are arranged on the housing, wherein the depth-of-field camera 51 is used for acquiring a local three-dimensional cloud image, specifically, the depth-of-field camera 51 can be provided with two groups, one group can be a first camera used for identifying a low-resolution depth image, and a second camera providing stereoscopic vision, the two groups of cameras are fused and shot to form the local three-dimensional cloud image, and the local three-dimensional cloud image is used for calculating a surface normal map, so that the posture of the current robot is estimated.
The laser radar 52 is used for acquiring the distance between the local characteristic point and the robot; specifically, the distance between the robot and the surface of the feature points, each of which may be understood as a landmark, may be output by the laser radar 52, and the local feature points may include a plurality of feature points, where the greater the number of feature points, the more accurate the estimation of the relative position coordinates of the robot.
A filter 6, preferably an extended kalman filter, disposed within the housing 1; the filter is used for acquiring the real-time position and the attitude of the local feature point relative to the robot according to the motion state of the robot; the motion state of the robot comprises the acceleration, the angular velocity and the displacement of the robot in the current state.
The ROS module 7 is arranged in the shell 1 and used for constructing an indoor map according to the local three-dimensional cloud picture and the distance between the local characteristic point and the robot; the method comprises the steps that an instruction of an external terminal moves to a target position of an indoor map to drive a purification assembly to purify air, specifically, after the indoor map is built, the indoor map can be reported to a mobile phone through a wireless communication module, the positions of all areas of the indoor environment are marked in a mobile phone APP according to the indoor environment, such as a kitchen, a living room and the like, for example, after the position of the kitchen area is determined, a certain position of the kitchen area is used as a target position, a target track for purifying air in the kitchen area is planned on the mobile phone APP, then target position instruction information is issued to an ROS module through the wireless communication module, the ROS module drives a hub motor to drive a driving wheel to rotate according to the target position instruction information, so that a robot is driven to move to the kitchen area, then air purification is carried out according to the target track, and the air purifier can be remotely opened and closed through the mobile phone APP, thereby purifying the air in the kitchen area; realizes full-automatic purification, enlarges the purification range and improves the purification efficiency.
Preferably, the sensor module 4 further comprises an ultrasonic module 53 for detecting obstacles in front of the robot, and a cliff sensor 54 for detecting a height difference of the working platform, and sending a signal to the ROS module when detecting a step or a high place, and the ROS module controls the robot to stop moving so as to prevent the robot from slipping from the high place.
Preferably, the ultrasonic module 53 includes 3 ultrasonic detectors, and the ultrasonic detectors are disposed on the housing.
Example two:
the embodiment provides a map building method based on the photocatalyst mobile robot, as shown in fig. 3, the map building method includes,
step S100: acquiring displacement, acceleration and speed of the robot; the displacement of robot is acquireed to the number of turns of rotation of accessible in-wheel motor, can calculate the acceleration, the speed of robot through the time of passing through.
Step S101: the distance and the angle between the local characteristic point and the robot can be obtained through the laser radar 52; the measurement range of the laser radar 52 is 0-360 degrees, the horizontal resolution is 0.2 degrees, and the laser radar 52 can realize full-circle scanning through the frequency of 10-100 HZ.
Step S102: acquiring the real-time position and posture of the local characteristic point relative to the robot according to the displacement, the acceleration and the speed of the robot and the distance and the angle between the local characteristic point and the robot so as to generate a first grid map; the local feature points represent a plurality of landmarks within the detection range of lidar 52;
step S103: acquiring a local image through the depth-of-field camera 51 to generate a local three-dimensional cloud picture, wherein the local image represents a three-dimensional image in a local range which can be detected by the depth-of-field camera 51, and calculating a surface normal map through scene surface points to estimate the real-time posture of the robot according to the real-time posture of the robot; performing nonlinear optimization according to the real-time attitude, and then performing loop detection; finally, establishing a local three-dimensional cloud picture;
step S104: optimizing the local three-dimensional cloud picture, eliminating false obstacle information, and projecting the optimized three-dimensional cloud picture to form a second grid picture; the first grid map and the second grid map are both 2D maps;
step S105: fusing the first grid map and the second grid map to generate an indoor map;
the first grid graph and the second grid graph are both composed of a plurality of grids, and the state of each grid is occupied or empty; for example, in a certain grid region in the first grid map, the ratio of the occupied area to the total grid area is higher than a preset threshold (e.g., 50%), which means that the state of the grid is occupied, and the ratio of the occupied area to the total grid area is lower than the preset threshold, which means that the state of the grid is empty.
If the states of the grids of the first grid map and the second grid map are both empty, determining that the state of the grid is empty;
if the states of the grids of the first grid map and the second grid map are occupied, determining that the states of the grids are occupied;
if the state of the grid of the first grid map is occupied and the state of the grid of the second grid map is empty, determining that the grid is occupied;
and if the state of the grid of the first grid map is empty and the state of the grid of the second grid map is occupied, determining that the grid is occupied.
When data association is performed in practical applications, we may encounter the following problems:
1. a feature point may be seen last but not next;
2. the feature point may be seen this time, but not later;
the above problems will cause serious problems for our navigation and mapping; because the depth-of-field camera 51 and the laser radar 52 have certain detection blind areas during monitoring, the first grid map and the second grid map are fused, so that the detection blind areas are reduced, the integrity of detected characteristic points is improved, and the two problems are greatly avoided.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (5)
1. A photocatalyst mobile robot, characterized by comprising:
a housing: comprises a shell and a chassis arranged at one end of the shell;
the wireless communication module is arranged in the shell and is used for being in wireless connection with an external terminal;
the moving assembly is arranged on the chassis and used for moving the robot;
the purification assembly comprises an air inlet and an air outlet which are arranged on the surface of the shell; and an air purifier mounted within the housing;
the sensor module comprises a depth-of-field camera and a laser radar, wherein the depth-of-field camera and the laser radar are arranged on the shell, the depth-of-field camera is used for acquiring a local three-dimensional cloud picture, and the laser radar is used for acquiring the distance between a local characteristic point and the robot;
the filter is arranged in the shell and used for acquiring the real-time position and the attitude of the local characteristic point relative to the robot according to the motion state of the robot; the motion state of the robot comprises the acceleration, the angular velocity and the displacement of the robot in the current state;
the ROS module is arranged in the shell and used for constructing an indoor map according to the local three-dimensional cloud picture and the distance between the local characteristic point and the robot; so as to move to the target position of the indoor map according to the instruction of the external terminal and drive the purification component to purify the air.
2. The photocatalyst mobile robot as claimed in claim 1, wherein the sensor module further comprises an ultrasonic module for detecting an obstacle in front of the robot, and a cliff sensor for detecting a height difference of the work platform.
3. The photocatalyst mobile robot as claimed in claim 1, wherein the ultrasonic module includes 3 ultrasonic detectors, and the ultrasonic detectors are disposed on the housing.
4. The photocatalyst mobile robot as claimed in claim 1, wherein the moving member includes two driving wheels, a hub motor disposed in the driving wheels, and four auxiliary universal wheels disposed around the base plate.
5. A map construction method based on the photocatalyst mobile robot as claimed in any one of claims 1 to 4, characterized in that the method comprises,
acquiring displacement, acceleration and speed of the robot;
obtaining the distance and the angle between the local characteristic point and the robot through a laser radar;
acquiring the real-time position and posture of the local characteristic point relative to the robot according to the displacement, the acceleration and the speed of the robot and the distance and the angle between the local characteristic point and the robot so as to generate a first grid map; the local feature points represent a plurality of landmarks within a detection range of the lidar;
acquiring a local image through a depth-of-field camera to generate a local three-dimensional cloud image;
projecting the local three-dimensional cloud image to form a second grid image;
fusing the first grid map and the second grid map to generate an indoor map;
the first grid graph and the second grid graph are both composed of a plurality of grids, and the state of each grid is occupied or empty;
if the states of the grids of the first grid map and the second grid map are both empty, determining that the state of the grid is empty; and judging the other situations as occupation.
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| CN202111066245.0A CN113741473A (en) | 2021-09-13 | 2021-09-13 | Photocatalyst mobile robot and map construction method |
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| CN202111066245.0A CN113741473A (en) | 2021-09-13 | 2021-09-13 | Photocatalyst mobile robot and map construction method |
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| CN106909156A (en) * | 2017-03-30 | 2017-06-30 | 北京小米移动软件有限公司 | Air purification method and device |
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2021
- 2021-09-13 CN CN202111066245.0A patent/CN113741473A/en active Pending
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| US20130226344A1 (en) * | 2012-02-29 | 2013-08-29 | Irobot Corporation | Mobile Robot |
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