CN108803588A - The control system of robot - Google Patents
The control system of robot Download PDFInfo
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- CN108803588A CN108803588A CN201710295472.8A CN201710295472A CN108803588A CN 108803588 A CN108803588 A CN 108803588A CN 201710295472 A CN201710295472 A CN 201710295472A CN 108803588 A CN108803588 A CN 108803588A
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- robot
- barrier
- sensor
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- control system
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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 or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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 or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
- G05D1/0242—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means using non-visible light signals, e.g. IR or UV signals
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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 or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- 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
Abstract
The invention discloses a kind of control system of robot, the system includes：Detection of obstacles module, the barrier data for environment where obtaining robot；Barrier processing module is handled for the barrier data to acquisition, obtains robot localization and/or the electronic map of navigation；Navigation control module plans the scheme of the robot movement for the electronic map according to task category and acquisition, and controls the robot movement and go execution task.The detection of obstacles module includes single or multiple sensors, barrier processing module formulates different processing schemes to different sensors signal, different signal classifications, and control robot further according to different task classification executes different strategies to barrier and robot movement.Method disclosed by the invention can optimize robot localization, navigation programming performance, promote user experience.
Description
Technical field
The present invention relates to robot building technical field, more particularly to a kind of control system of robot.
Background technology
With the continuous improvement of domestic level, robot enters into ordinary citizen house as the popular vehicles, and is connect by more and more people
By, for example, sweeping robot as cleaning helper, can obstruction detection, such as encounter wall or other barriers, can voluntarily turn
Curved, existing robot generally uses and synchronizes the method for the positioning for building figure and provide navigation programming map and positioning for mobile robot
Information.
However, barrier is uniformly processed in existing robot, for example, it may be possible to mobile desk or fixed bed, when
Can mobile desk when moving, still influence navigation programming or the long-standing static-obstacle thing for being not easy to observe in real time
It can still knock so that robot seems that some are not clever and not intelligent.
Invention content
The present invention is directed to solve at least to a certain extent it is above-mentioned in the related technology the technical issues of one of.
For this purpose, an object of the present invention is to provide a kind of control methods of robot.The control method of the robot
Optimize robot localization, navigation programming performance, promotes user experience.
To achieve the goals above, an aspect of of the present present invention discloses a kind of control system of robot, which includes：
Detection of obstacles module, the barrier data for environment where obtaining robot；Barrier processing module, for acquisition
Barrier data are handled, and robot localization and/or the electronic map of navigation are obtained；Navigation control module is appointed for basis
Classification of being engaged in and the electronic map of acquisition, plan the scheme of the robot movement, and control the robot movement and go to execute
Task.
The control system of robot according to the present invention, by analyte detection module of placing obstacles in robot with detection machine
The obstacle information of environment where device people, and obstacle information is reasonably handled, it obtains as robot localization and/or leads
Boat electronic map used, with according to task type and electronic map, the mobile scheme of planning robot, to optimize machine
The positioning of people, navigation programming performance, the user experience is improved.
In addition, the control system of robot according to the above embodiment of the present invention can also have following additional technology special
Sign：
Further, the detection of obstacles module includes：The type of single or multiple sensors, the sensor can not
Together, including：Distance measuring sensor can detect distance and bearing of the barrier relative to sweeper；Or crash sensor, it can be in machine
Collision alarm is detected when collision obstacle；Or Inertial Measurement Unit, acceleration when measurable machine moves or angular speed letter
Number.
Further, the distance measuring sensor includes：Laser radar sensor and/or depth camera sensor, and/or
Infrared wall inspection sensor and/or infrared along wall sensor and/or ultrasonic distance-measuring sensor.
Further, the barrier processing module includes：Confidence level handles submodule, for according to the obstacle quality testing
It surveys the detection data of multiple sensors of module and obtains the robot corresponding to the confidence level weights of each sensor
Barrier in scope of activities, wherein the multiple sensor corresponds respectively to multiple and different confidence level weights.
Further, when detection of obstacles module is distance measuring sensor, the data confidence power of the distance measuring sensor
Value is weighted processing by from the robot to the distance of the barrier, and distance is bigger, and confidence value is lower.
Further, the barrier processing module further includes：Identify submodule, for identification the class of the barrier
Type, wherein the type of the barrier includes dynamic barrier or static-obstacle thing, and is the machine according to recognition result
People plans navigation map and/or positioning.
Further, the method for identifying the type of the barrier includes：Sentenced according to background modeling method or frame difference method
Whether the barrier that breaks is subjected to displacement, if it is, being the dynamic barrier, if it is not, then being the static-obstacle thing；
And/or detect whether the number of barrier is more than preset threshold value in fixed position according to different time, if it is, being
The static-obstacle thing, if it is not, then being the dynamic barrier.
Further, the navigation control module is specifically used for：The task type is to be believed to a movement according to barrier
Breath, is planned for a movement navigation path, wherein the path collides far from barrier to avoid robot.
Further, the navigation control module is specifically used for：The task type is cleaning, controls the robot and exists
Collide or close to obstacle distance to predetermined threshold value when, in navigation programming it is corresponding at the barrier increase along side
Walking navigation is planned.
Further, the navigation control module is specifically used for：The barrier bottle up the robot when, to the machine
Device people implements to escape task；When escaping task described in execution, controls the robot and remove the week recorded in the navigation map
The obstacle information enclosed opens the navigation of all directions, records obstacle information again, until escaping success；If repeatedly escaped
Depigmentation loses, and judges that robot is bottled up completely, stranded information is reported to seek assist process.
The additional aspect and advantage of the present invention will be set forth in part in the description, and will partly become from the following description
Obviously, or practice through the invention is recognized.
Description of the drawings
The above-mentioned and/or additional aspect and advantage of the present invention will become in the description from combination following accompanying drawings to embodiment
Obviously and it is readily appreciated that, wherein：
Fig. 1 is the structure diagram of the control system of robot according to an embodiment of the invention；
Fig. 2 is the signal of robot installation laser radar sensor and crash sensor according to an embodiment of the invention
Figure；And
Fig. 3 is barrier classification schematic diagram according to an embodiment of the invention.
Specific implementation mode
The embodiment of the present invention is described below in detail, examples of the embodiments are shown in the accompanying drawings, wherein from beginning to end
Same or similar label indicates same or similar element or element with the same or similar functions.Below with reference to attached
The embodiment of figure description is exemplary, and is only used for explaining the present invention, and is not considered as limiting the invention.
The control system of robot according to the ... of the embodiment of the present invention is described below in conjunction with attached drawing.
Fig. 1 is the structure diagram of the control system of robot according to an embodiment of the invention.
As shown in Figure 1, the control system 100 of robot according to an embodiment of the invention, including：Detection of obstacles mould
Block 110, barrier processing module 120 and navigation control module 130.
Wherein, the barrier data of environment where detection of obstacles module 110 is used to obtain robot.Barrier handles mould
Block 120 obtains robot localization and/or the electronic map of navigation for handling the barrier data of acquisition.Navigation control
Molding block 130 is used for the electronic map according to task category and acquisition, the scheme of planning robot's movement, and controls robot
Execution task is gone in movement.In addition, the system 100 can also include：Mobile module is used for mobile robot.
The control system of robot according to the present invention, by analyte detection module of placing obstacles in robot with detection machine
The obstacle information of environment where device people, and obstacle information is reasonably handled, it obtains as robot localization and/or leads
Boat electronic map used, with according to task type and electronic map, the mobile scheme of planning robot, to optimize machine
The positioning of people, navigation programming performance, the user experience is improved.
In some embodiments, detection of obstacles module 110 includes：The type of single or multiple sensors, sensor can
Difference, including：Distance measuring sensor can detect distance and bearing of the barrier relative to sweeper, be typically mounted at robot
On top or crash sensor, it can detect collision alarm in machine collision obstacle, be typically mounted at the side of robot
On or Inertial Measurement Unit, acceleration or angular velocity signal when the movement of measurable machine.Wherein, distance measuring sensor includes：Swash
Optical radar sensor and/or depth camera sensor and/or infrared wall inspection sensor and/or infrared along wall sensor, and/
Or ultrasonic distance-measuring sensor.Wherein, infrared wall inspection sensor with it is infrared along wall sensor can make as sensor, but
It is that installation site is different, function is different.
Specifically, robot may include multiple sensors for detecting barrier, and the type of multiple sensors can
With difference, a type of sensor can be installed, the sensor of several types can also be combined be installed to it is same
In robot.As shown in Fig. 2, being mounted with two sensors in robot, one is laser radar sensor, and one is collision
Sensor, and laser radar sensor belongs to distance measuring sensor this type, that is to say, that the robot in Fig. 2 is mounted with two
The sensor of type.
In some embodiments, barrier processing module 120 includes：Confidence level handles submodule, for according to barrier
The detection data of multiple sensors of detection module 110 and obtain robot corresponding to the confidence level weights of each sensor
Barrier in scope of activities, wherein multiple sensors correspond respectively to multiple and different confidence level weights.
In other words, these different types of sensor characteristics are different, then pass through the meaning of the barrier measured by sensor
Justice is also just different, and the purposes of the confidence level processing submodule is exactly to be weighed configured with different confidence levels to different sensors
Value.
As an example, the sensor being mounted in robot can be crash sensor, and confidence level submodule is touched
It hits the data that sensor detects and carries out maximum weighting processing.Because only that the barrier of physical presence can just collide, because
The data of this crash sensor record have absolute reliability, give maximum weights.
Further, when detection of obstacles module 110 is distance measuring sensor, the data confidence weights of distance measuring sensor
It is weighted processing by the distance from robot to barrier, distance is bigger, and confidence value is lower.
As an example, the sensor being mounted in robot is laser radar sensor, to laser radar sensor
Detection data be weighted processing by the distance from robot to barrier, distance is bigger, and weights are lower.Because of laser radar
The finding range of sensor generally has a blind area, and at a distance when error will increase, therefore laser radar sensor should be given
Detection data increasing different distance it is different weights distribution, confidence value is low when remote, and the data in blind area are set
Reliability is zero.Formulate different strategies in the position that can be also measured according to detection data.
Wherein, the crash sensor either aiding sensors of depth camera or IMU as laser radar sensor.Specifically
For, in conjunction with shown in Fig. 2, the data that the laser radar sensor as detects are single line of data, are only capable of detecting laser radar
The barrier on threshold level line that sensor is detected, then for threshold level line barrier below, laser radar sensing
Device may not play effect, then then needing to assist other sensors such as crash sensor record other influences robot row
The lower obstacle information walked.Wherein, the barrier of entire surface can also be measured with depth camera, and according to the knot of robot
Structure information calculates the barrier for influencing robot ambulation, and is projected.It can also be less than with the IMU data records recorded
The barriers such as the ground protrusion of crash sensor make next robot slow down when these out-of-flatness regions are walked.IMU
Crash sensor can also be replaced, detects whether to collide.Significantly, since the barrier on the positioning map of robot
Obstacle information in information and navigation map has difference, according to the mission requirements of positioning map, can only use real-time remote
The data of the sensor detection of observation are positioned, and laser radar sensor or depth camera are such as used.
Wherein, robot detection barrier signal source can also be infrared distance measurement, ultrasonic wave, survey sensor,
Odometer etc. is that robot establishes navigation picture and positioning with auxiliary.
In some embodiments, barrier processing module 120 further includes：Identify submodule, for identification the class of barrier
Type, wherein the type of barrier includes dynamic barrier or static-obstacle thing, and is led for robot planning according to recognition result
Boat map and/or positioning.
Further, the method for the type of cognitive disorders object includes：Judge barrier according to background modeling method or frame difference method
Hinder whether object is subjected to displacement；If it is, being dynamic barrier；If it is not, then being static-obstacle thing.And/or according to it is different when
Between fixed position detect barrier number whether be more than preset threshold value, if it is, be the static-obstacle thing, such as
Fruit is no, then is the dynamic barrier.
In conjunction with shown in Fig. 3,102 movement artificial dynamic barriers, 103 chairs be can mobile barrier, 104 are
Static-obstacle thing.
For specific example, laser radar sensor or depth camera data are installed in robot, pass through background modeling
Method or frame difference method method detection object whether be movement, if detecting has the object of movement in barrier, judge
The dynamic barrier when barrier.If motionless, to prevent error detection, then during the motion, point in different times, same
The position of sample detects the barrier, and the number detected has been more than preset threshold value, then it is assumed that detected
Barrier be static-obstacle thing, if it is not, thinking that detected barrier is dynamic barrier.And it can be by this
A little information are added in navigation map, and static-obstacle thing or dynamic are either identified when executing task orientation robot location
Barrier.For example, the recognition result of barrier can be recorded on navigation map, realize to common mobile robot control
System, wherein static-obstacle thing can influence path planning, and robot can get around walking, and dynamic barrier does not influence robot path
Planning is slowed down then being controlled when robot is close to dynamic barrier, and attempts to travel through dynamic barrier walking.It is advised for robot
Environment Obstacles object location information, robot can move the area of clear where what is recorded when drawing navigation map, on map have
The region that domain and unknown machine people do not explore.
Further, further include：When the type change of barrier, going through for the barrier of the corresponding type that changes is removed
History information, and be identified again.For example, if dynamic barrier has disappeared, the obstacle of record can be removed directly through walking
Object information.If still existing, barrier can trigger crash sensor or the sensors such as infrared sensor or ultrasonic wave, mark obstacle
The presence of object.If robot measures some during walking according to task becomes accessible labeled as the region of barrier
Object then quickly removes the historical information of the region barrier, it is believed that clear at this can be removed be erroneously interpreted as in this way
The region of barrier, to achieve the purpose that real-time update barrier.
As an example, navigation control module 130 is specifically used for：Task type is to be believed to a movement according to barrier
Breath, is planned for a movement navigation path, wherein path far from barrier, avoids robot from colliding as possible.Such as from control
Robot is moved from A points to B points, then the obstacle information that can be detected according to detection of obstacles module 110, is planned from A points
To the distance of B points so that there is a certain distance between the path of planning and the barrier detected, avoid colliding, this
Sample, which is done, can preferably protect robot.
As an example, navigation control module 130 is specifically used for：Task type is cleaning, and control robot is colliding
Arrive or close to obstacle distance to predetermined threshold value when, in navigation programming at the corresponding barrier increase along side walking lead
Boat planning.For example, the task of sweeper is desirable to be swept into all regions as possible, the especially area more than the barrier of side corner angle
Domain, sweeper can open the presence for only colliding every time and just thinking barrier, what the robot unlatching after collision was cleaned along side
Task along barrier rotation clean until the path of the preplanning gone to along side, or planning path is walked again.
As an example, navigation control module 130 is specifically used for：Barrier bottle up robot when, to robot implement
Escape task；When task is escaped in execution, control robot removes the obstacle information that surrounding is recorded in navigation map, opens each
The navigation in a direction, records obstacle information again, until escaping success；If repeatedly escaping failure, robot quilt is judged
It bottles up completely, stranded information is reported to seek assist process.
Specifically, navigation control module 130 needs different control strategies according to the task of setting.In particular,
When mobile robot is caught in, since the data of barrier have been recorded in various situations, subsequent path planning is influenced whether.Such as
Fruit robot has been played with for a long time by some dynamic barrier, for example, people, it is likely that dynamic barrier is marked as static-obstacle
Object causes to be caught in.Therefore, when encountering robot and being caught in, task is escaped to robot implementation, robot should be first clear
Except the obstacle information of surrounding, the navigation programming of all directions is opened, according to detection of obstacles module 110 during walking
(for example, crash sensor) records the position of sensor again, until finding an exit and getting rid of poverty, so as to improve different task
Make that algorithm effect is more preferable when demand.Wherein, the navigation of all directions is opened, robot attempts all directions and is escaped,
The sequence for attempting direction can be to carry out escaping for comprehensive no dead angle from direction clockwise or counter-clockwise.
The control system of robot according to the present invention, by analyte detection module of placing obstacles in robot with detection machine
The obstacle information of environment where device people, and obstacle information is reasonably handled, it obtains as robot localization and/or leads
Boat electronic map used, with according to task type and electronic map, the mobile scheme of planning robot, to optimize machine
The positioning of people, navigation programming performance, the user experience is improved.
In addition, term " first ", " second " are used for description purposes only, it is not understood to indicate or imply relative importance
Or implicitly indicate the quantity of indicated technical characteristic.Define " first " as a result, the feature of " second " can be expressed or
Implicitly include at least one this feature.In the description of the present invention, the meaning of " plurality " is at least two, such as two, three
It is a etc., unless otherwise specifically defined.
In the present invention unless specifically defined or limited otherwise, term " installation ", " connected ", " connection ", " fixation " etc.
Term shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or integral；Can be that machinery connects
It connects, can also be electrical connection；It can be directly connected, can also can be indirectly connected through an intermediary in two elements
The interaction relationship of the connection in portion or two elements, unless otherwise restricted clearly.For those of ordinary skill in the art
For, the specific meanings of the above terms in the present invention can be understood according to specific conditions.
In the description of this specification, reference term " one embodiment ", " some embodiments ", " example ", " specifically show
The description of example " or " some examples " etc. means specific features, structure, material or spy described in conjunction with this embodiment or example
Point is included at least one embodiment or example of the invention.In the present specification, schematic expression of the above terms are not
It must be directed to identical embodiment or example.Moreover, particular features, structures, materials, or characteristics described can be in office
It can be combined in any suitable manner in one or more embodiments or example.In addition, without conflicting with each other, the skill of this field
Art personnel can tie the feature of different embodiments or examples described in this specification and different embodiments or examples
It closes and combines.
Although the embodiments of the present invention has been shown and described above, it is to be understood that above-described embodiment is example
Property, it is not considered as limiting the invention, those skilled in the art within the scope of the invention can be to above-mentioned
Embodiment is changed, changes, replacing and modification.
Claims (10)
1. a kind of control system of robot, which is characterized in that including：
Detection of obstacles module, the barrier data for environment where obtaining robot；
Barrier processing module is handled for the barrier data to acquisition, obtains robot localization and/or the electricity of navigation
Sub- map；
Navigation control module plans the scheme of the robot movement for the electronic map according to task category and acquisition,
And it controls the robot movement and goes execution task.
2. the control system of robot according to claim 1, which is characterized in that the detection of obstacles module includes：
The type of single or multiple sensors, the sensor can be different, including：
Distance measuring sensor can detect distance and bearing of the barrier relative to sweeper；
Or crash sensor, it can detect collision alarm in machine collision obstacle；
Or Inertial Measurement Unit, acceleration or angular velocity signal when measurable machine moves.
3. the control system of robot according to claim 2, which is characterized in that the distance measuring sensor includes：
Laser radar sensor, and/or
Depth camera sensor, and/or
Infrared wall examines sensor, and/or
It is infrared along wall sensor, and/or
Ultrasonic distance-measuring sensor.
4. the control system of robot according to claim 1, which is characterized in that the barrier processing module includes：
Confidence level handles submodule, is used for the detection data and correspondence of multiple sensors according to the detection of obstacles module
The barrier in the scope of activities of the robot is obtained in the confidence level weights of each sensor, wherein the multiple sensing
Device corresponds respectively to multiple and different confidence level weights.
5. the control system of robot according to claim 4, which is characterized in that when detection of obstacles module passes for ranging
When sensor, the data confidence weights of the distance measuring sensor are weighted by from the robot to the distance of the barrier
Processing, distance is bigger, and confidence value is lower.
6. the control system of robot according to claim 1, which is characterized in that the barrier processing module is also wrapped
It includes：
Identify submodule, for identification type of the barrier, wherein the type of the barrier include dynamic barrier or
Person's static-obstacle thing, and be the robot planning navigation map and/or positioning according to recognition result.
7. the control system of robot according to claim 6, which is characterized in that identify the side of the type of the barrier
Method includes：
Judge whether the barrier is subjected to displacement according to background modeling method or frame difference method, if it is, being the dynamic
Barrier, if it is not, then being the static-obstacle thing；
And/or detect whether the number of barrier is more than preset threshold value in fixed position according to different time, if so,
It is then the static-obstacle thing, if it is not, then being the dynamic barrier.
8. the control system of robot according to claim 1, which is characterized in that the navigation control module is specifically used
In：
The task type is, according to obstacle information, to be planned for a movement navigation path, wherein the path to a movement
Far from barrier, collide to avoid robot.
9. the control system of robot according to claim 1, which is characterized in that the navigation control module is specifically used
In：The task type is cleaning, controls the robot when colliding or close to obstacle distance to predetermined threshold value, is leading
Increase at the corresponding barrier in boat planning and is planned along side walking navigation.
10. the control system of robot according to claim 1, which is characterized in that the navigation control module is specifically used
In：
The barrier bottle up the robot when, to the robot implementation escape task；
When escaping task described in execution, controls the robot and remove the barrier letter for recording surrounding in the navigation map
Breath, opens the navigation of all directions, records obstacle information again, until escaping success；
If repeatedly escaping failure, judges that robot is bottled up completely, stranded information is reported to seek assist process.
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| CN111061215A (en) * | 2019-12-26 | 2020-04-24 | 北京市商汤科技开发有限公司 | Method and device for controlling robot to get rid of poverty and robot |
| CN113552589A (en) * | 2020-04-01 | 2021-10-26 | 杭州萤石软件有限公司 | Obstacle detection method, robot, and storage medium |
| CN111813123A (en) * | 2020-07-17 | 2020-10-23 | 徐州泰丰泵业有限公司 | Sprinkling irrigation machine walking control system and control method |
| CN114052561A (en) * | 2020-08-01 | 2022-02-18 | 尚科宁家(中国)科技有限公司 | Self-moving robot |
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| CN112562280A (en) * | 2020-12-08 | 2021-03-26 | 广州赛特智能科技有限公司 | Robot alarm method and system |
| CN112650228A (en) * | 2020-12-14 | 2021-04-13 | 苏州阿甘机器人有限公司 | AGV robot obstacle detection device and working method thereof |
| CN112859873B (en) * | 2021-01-25 | 2022-11-25 | 山东亚历山大智能科技有限公司 | Semantic laser-based mobile robot multi-stage obstacle avoidance system and method |
| CN112859873A (en) * | 2021-01-25 | 2021-05-28 | 山东亚历山大智能科技有限公司 | Semantic laser-based mobile robot multi-stage obstacle avoidance system and method |
| CN113741467B (en) * | 2021-09-07 | 2023-10-13 | 深圳大方智能科技有限公司 | Vertical wall surface construction method and construction robot |
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