CN113848918A - Robot rapid, efficient and low-cost deployment method and system - Google Patents
Robot rapid, efficient and low-cost deployment method and system Download PDFInfo
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- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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- G05D1/02—Control of position or course in two dimensions
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Abstract
The invention provides a rapid, efficient and low-cost deployment method and system for a robot, which comprises the following steps: step 1: scanning by a drawing robot, and collecting environmental data; step 2: constructing a map according to the collected environmental data; and step 3: judging the definition of the map, and carrying out map repairing and point position taking according to the definition; and 4, step 4: and (4) carrying out elevator control and telephone system installation, and carrying out test and operation training. The invention adopts a distributed scheme, decouples the steps of on-site map scanning, map point location repairing, on-site training delivery and the like, greatly improves the deployment efficiency by a pipeline mode, greatly reduces the deployment time of personnel, simultaneously reduces the technical requirement of the deployment personnel, and realizes that professional personnel do professional work.
Description
Technical Field
The invention relates to the technical field of robots, in particular to a rapid, efficient and low-cost deployment method and system for a robot.
Background
At present, the technologies of the delivery robot and the cleaning robot are more and more mature, the use amount of the robots in the market is more and more large, and the field deployment speed of the robots cannot keep pace with the actual delivery amount, so that a method for rapid field deployment is needed to solve the problem.
Patent document CN111124438A (application number: CN201911292397.5) discloses a deployment method of enterprise foreground robots, which includes the following steps: s1: environmental investigation; s2: planning and designing; s3: the method comprises the following steps of mapping and area division, wherein a system supplier arranges engineering personnel to draw a sketch of a foreground coverage area according to a scene on site and indicates each area; s4: building a map of LAM; s5: the map building environment is improved; s6: configuring a map; s7: deploying a local server: building a server and implementing deployment; s8: and (5) delivering to run.
Patent document CN106443583A (application number: CN201610784535.1) discloses a location-based regional optical label rapid deployment method, which includes: 1) initially deploying an optical label in an area to be deployed; 2) placing a plurality of robots in an area to be deployed, wherein each robot is provided with a mobile identification device based on optical label positioning; 3) the robot carries out random walk traveling in an area to be deployed, in the traveling process of the robot, mobile identification equipment based on optical label positioning on the robot positions the robot, and when the positioning is successful, the robot continues to travel; when the positioning is not successful, the robot stops moving, the area where the robot is located at present is marked as a positioning blind area, and the step 4) is executed; when the robot traverses the area to be deployed with the optical labels and no positioning blind area is found, the deployment of the optical labels is completed; 4) and deploying the optical labels according to the shape of the positioning blind area, and turning to the step 3).
Taking the hotel delivery robot field deployment example, the process is as follows: 1) the machine is shipped by the factory to the customer; 2) a technician enters a field after receiving goods by a client, pushes the robot to build a drawing layer by layer; 3) after the map is built, the map needs to be corrected within a certain time; 4) after the map is corrected, a technician pushes the robot to each room gate to carry out room point positioning; 5) elevator control deployment and program-controlled telephone system deployment; 6) testing, training and delivering.
However, the following drawbacks exist:
a. when the map is built, the machine body is pushed to build the map, the body is generally heavy, a hotel corridor generally has a thick floor, the resistance is large, the pushing is very laborious, and if the control is not good, the machine body is easy to tilt forwards, and the laser scans the ground, so that the generated two-dimensional map is disordered;
b. the slam graph building needs operators to have knowledge of relevant backgrounds, and the operators who are not trained by the system cannot work;
c. the field personnel need to correct the map on the field and then push the machine to the door of the room to get the room, if the process can be processed in the background, the time of the field personnel is not occupied, and the deployment time is greatly accelerated;
d. generally, after a machine system is stable, cost can be reduced through multiple rounds, body hardware and system resources are just enough, once a large complex scene is met, a relatively good sensor and relatively more computer computing power are needed to construct a relatively ideal two-dimensional map, repeated map construction is carried out for many times, and the time for modifying the map is increased.
The defects can prolong the field deployment time, increase the enterprise cost and greatly reduce the deployment efficiency.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a rapid, efficient and low-cost deployment method and system for a robot.
The robot deployment method with high speed, high efficiency and low cost provided by the invention comprises the following steps:
step 1: scanning by a drawing robot, and collecting environmental data;
step 2: constructing a map according to the collected environmental data;
and step 3: judging the definition of the map, and carrying out map repairing and point position taking according to the definition;
and 4, step 4: and (4) carrying out elevator control and telephone system installation, and carrying out test and operation training.
Preferably, the building is scanned layer by layer in a remote control mode, data collected by a laser radar and an inertial sensor which are installed on the mapping robot are encoded through an encoder, a data packet is generated, and the data packet is uploaded to a server according to a preset format.
Preferably, reading the corresponding data packet in the server, acquiring laser data and odometer data at the current moment, performing laser matching by using the odometer value as an initial value to obtain a calibrated position, generating a grid map by using the laser data, generating constraints between each frame and each sensor, and performing loop optimization according to a preset frequency;
and (4) repairing the map according to the uploaded pictures and the description information, and storing the map in a map server after finishing repairing the map on all floors.
Preferably, whether room points need to be collected is judged according to the actual situation of the map, and if the definition of the outline of the room door is within a preset range, the points are directly taken and stored in the server; and if the definition of the outline of the room door exceeds the preset range, re-taking the point location and building the icon point.
Preferably, after the icon point is built, the map and the room point locations are downloaded from the server, the elevator points, the avoidance points and the elevator waiting points are automatically checked through a preset program, and secondary checking is carried out on the room points.
The robot deployment system provided by the invention has the advantages that:
module M1: scanning by a drawing robot, and collecting environmental data;
module M2: constructing a map according to the collected environmental data;
module M3: judging the definition of the map, and carrying out map repairing and point position taking according to the definition;
module M4: and (4) carrying out elevator control and telephone system installation, and carrying out test and operation training.
Preferably, the building is scanned layer by layer in a remote control mode, data collected by a laser radar and an inertial sensor which are installed on the mapping robot are encoded through an encoder, a data packet is generated, and the data packet is uploaded to a server according to a preset format.
Preferably, reading the corresponding data packet in the server, acquiring laser data and odometer data at the current moment, performing laser matching by using the odometer value as an initial value to obtain a calibrated position, generating a grid map by using the laser data, generating constraints between each frame and each sensor, and performing loop optimization according to a preset frequency;
and (4) repairing the map according to the uploaded pictures and the description information, and storing the map in a map server after finishing repairing the map on all floors.
Preferably, whether room points need to be collected is judged according to the actual situation of the map, and if the definition of the outline of the room door is within a preset range, the points are directly taken and stored in the server; and if the definition of the outline of the room door exceeds the preset range, re-taking the point location and building the icon point.
Preferably, after the icon point is built, the map and the room point locations are downloaded from the server, the elevator points, the avoidance points and the elevator waiting points are automatically checked through a preset program, and secondary checking is carried out on the room points.
Compared with the prior art, the invention has the following beneficial effects:
the invention adopts a distributed scheme, decouples the steps of on-site map scanning, map point location repairing, on-site training delivery and the like, greatly improves the deployment efficiency by a pipeline mode, greatly reduces the deployment time of personnel, simultaneously reduces the technical requirement of the deployment personnel, and realizes that professional personnel do professional work.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the detailed description of non-limiting embodiments with reference to the following drawings:
FIG. 1 is a flow chart of the method of the present invention;
fig. 2 is a schematic view of a small-sized figure-building robot.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that it would be obvious to those skilled in the art that various changes and modifications can be made without departing from the spirit of the invention. All falling within the scope of the present invention.
Example (b):
the invention adopts a distributed scheme, decouples the steps of on-site map scanning, map point location repairing, on-site training delivery and the like, greatly improves the deployment efficiency by a pipeline mode, greatly reduces the deployment time of personnel, simultaneously reduces the technical requirement of the deployment personnel, and realizes that professional personnel do professional work.
Referring to fig. 1, the robot deployment method with high efficiency and low cost provided by the present invention includes the following steps:
step 1: a small-sized mapping robot is carried by a mapping technician to carry out door scanning, and the small-sized mapping robot is composed of a high-precision laser radar, a high-precision imu, a high-precision encoder and an industrial personal computer, as shown in figure 2. The equipment is small in size, convenient to assemble and convenient to carry for technicians. The small-sized drawing building robot is moved one by a drawing scanner in a remote control mode, the robot does not perform drawing building operation when actually walking, only collects data of each sensor to generate data packets, generates one data packet of the layer when finishing one layer, uploads the data packets to a server according to a specified format and fills necessary information.
The method has the following advantages: 1) the special image scanning personnel carry equipment to collect data for the image forming module, and the user can leave the store without repairing images and taking points after the collection is finished; 2) the portable mapping machine has higher sensor precision, the quality of the collected data packet is good, and a good map can be generated; 3) by adopting a remote control mode, the defects of hand pushing are avoided, the robot is more stable, and the odometer data is more accurate.
Step 2: background staff receive tasks from work orders, directly read data packets needing mapping from a special mapping server, generate maps by using parameters with the strong optimal computing power of the server, modify the maps according to pictures, descriptions and the like uploaded by data acquisition staff, and store the maps in a map server after all floors are finished.
The method has the advantages that: 1) the server is adopted to run the graph building algorithm, so that the speed is high, the effect is good, and the precision is high; 2) background personnel do not need to arrive at the site, and the labor expenditure is saved.
And step 3: background personnel judge whether to gather the room point according to map actual conditions, if the room door profile is clear, then directly get the point and save to the server, if can't see the room door profile clearly, can wait to machine to the shop after, by the operation of installation training personnel, most scene elevator position, room position are very easy to be distinguished, and the deployment man-hour of field personnel can be saved greatly to background mark position.
And 4, step 4: after the icon point building process is completed, the machine delivers goods to the site, an engineer is installed to download a map and room point locations from a server, special point locations such as an elevator point, an avoidance point and a waiting point can be automatically checked through a program, and secondary checking is carried out on the room points.
And 5: when the robot delivers goods, an installer appoints an elevator maintenance to perform elevator control installation when the robot arrives at the same day, and the same day also comprises telephone system installation, robot map downloading and testing, and use training.
In conclusion, in robot deployment, the mapping link is the most time-consuming, and the mapping step is disassembled, so that a high-quality map can be obtained, manpower and material resources can be saved, and rapid, efficient, high-quality and low-cost deployment can be achieved.
Compared with a common industrial personal computer, the server has higher requirements on stability, safety, data processing capacity, high expansibility, I/O performance and the like.
When an environment is mapped, laser radar data, ultrasonic data, odometer data, visual imu data and the like need to be collected in real time, the frequency of each sensor is different from 10-300 Hz, the data need to be sampled, denoised, sequenced and aligned in time stamps, the data need to occupy larger memory for storage and data exchange when being processed, and the operation needs to be processed by a plurality of CPUs (central processing units) in a multi-process and multi-thread mode, so that the real-time performance of the server on the industrial personal computer of the robot body is higher when the data are processed, and the solution is faster when the iterative computation is carried out. The server hardware parameters currently in use are as follows: hard disk 4T, memory 32G, CPUintelXeon [email protected] core.
Generally, the corresponding adjustment parameters are determined in hardware to meet the requirements of different hardware. Taking an industrial personal computer and a server as examples, the use of the limited memory usage amount and the CPU usage core number is used when the robot body is used for building the image; a large amount of data is subjected to down sampling during data processing, and a plurality of characteristic points are filtered out in the down sampling process; when the data construction constraint connection is carried out, the frequency of generating the constraint is reduced, and the generated constraint condition is set to be stricter, such as distance, angle and the like. However, if a server with better hardware conditions is used for building the graph, resources can be used in a full load mode, the number of cpus is enough, the memory is large enough, down-sampling is not performed any more, the constraint generation frequency is increased, the constraint conditions are relaxed, and more data association is obtained. Therefore, the optimal parameters are adaptively adjusted according to the acquired change of the hardware:
keyframe sample distance Dis ═ T × a
Keyframe sampling angle Ang ═ T × b
Wherein: a is 1m, b is 10 DEG
T＝x-0.1
| Number of nuclei | T1 value | Taking two decimal places |
| 1 | 1 | round(1)＝1 |
| 2 | 0.933 | round(0.933)＝0.93 |
| 4 | 0.87 | round(0.87)＝0.87 |
| 8 | 0.812 | round(0.812)＝0.81 |
| 16 | 0.757 | round(0.757)＝0.75 |
Sampling frequency H ═ k × c
Constraint building frequency P ═ k × d
Wherein: c 1hz, d 1hz
k＝k1+k2
k1＝ln(x)+1，x>＝1
| Number of nuclei | k1 value | Get round upwards |
| 1 | 1 | ceil(1)＝1 |
| 2 | 1.69 | ceil(1.69)＝2 |
| 4 | 2.38 | ceil(2.38)＝3 |
| 8 | 3.07 | ceil(3.07)＝4 |
| 16 | 3.77 | ceil(3.77)＝4 |
| Memory device | k2 |
| memory<4G | 1 |
| 4G≤memory<8G | 2 |
| memory≥8G | 3 |
After the parameters are obtained, it is the standard slam process: and acquiring laser data and odometer data at the current moment, performing laser matching by using the odometer value as an initial value to obtain a calibrated position, generating a grid map by using the laser data, generating constraints between each frame and each sensor, and performing loop optimization according to a fixed frequency.
When recording a data packet by a professional map scanner in the step 1, photographing and marking can be carried out on the hotel, for example, a table with a hollowed-out opening is arranged at an elevator entrance, the data packet is uploaded together when being uploaded, a background person builds a map to obtain a grid map, burrs possibly exist on the edge of the map at the moment, a room door is opened, glass cannot pass through scanning due to laser, the conditions of slope, stairs and the like exist, the background person carries out manual map repairing on the map according to picture video characters and the like on a platform, the burrs are removed, the room door is connected by using black lines, a glass curtain wall is repaired by using a virtual wall, slope points are marked and fall at the slope and the stairs, and a robot executes a corresponding strategy when passing through the area.
Those skilled in the art will appreciate that, in addition to implementing the systems, apparatus, and various modules thereof provided by the present invention in purely computer readable program code, the same procedures can be implemented entirely by logically programming method steps such that the systems, apparatus, and various modules thereof are provided in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Therefore, the system, the device and the modules thereof provided by the present invention can be considered as a hardware component, and the modules included in the system, the device and the modules thereof for implementing various programs can also be considered as structures in the hardware component; modules for performing various functions may also be considered to be both software programs for performing the methods and structures within hardware components.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (10)
1. A robot deployment method with high speed, high efficiency and low cost is characterized by comprising the following steps:
step 1: scanning by a drawing robot, and collecting environmental data;
step 2: constructing a map according to the collected environmental data;
and step 3: judging the definition of the map, and carrying out map repairing and point position taking according to the definition;
and 4, step 4: and (4) carrying out elevator control and telephone system installation, and carrying out test and operation training.
2. The robot rapid, efficient and low-cost deployment method of claim 1, characterized in that a building is scanned layer by layer in a remote control manner, data collected by a laser radar and an inertial sensor installed on the robot for building a picture are encoded by an encoder, a data packet is generated and uploaded to a server according to a preset format.
3. The robot rapid, efficient and low-cost deployment method according to claim 2, characterized in that a corresponding data packet is read in a server, laser data and odometer data at the current moment are obtained, laser matching is performed by using an odometer value as an initial value to obtain a calibrated position, then a raster map is generated by using the laser data, constraints are generated between each frame and each sensor, and loop optimization is performed according to a preset frequency;
and (4) repairing the map according to the uploaded pictures and the description information, and storing the map in a map server after finishing repairing the map on all floors.
4. The robot rapid, efficient and low-cost deployment method according to claim 1, characterized in that whether room points need to be collected is judged according to the actual situation of a map, and if the definition of the outline of a room door is within a preset range, the points are directly taken and stored in a server; and if the definition of the outline of the room door exceeds the preset range, re-taking the point location and building the icon point.
5. The robot rapid, efficient and low-cost deployment method according to claim 4, characterized in that after the construction of the map points is completed, the map and the room points are downloaded from the server, and the elevator points, the avoidance points and the elevator waiting points are automatically checked through a preset program to perform secondary check on the room points.
6. A robot rapid, efficient and low cost deployment system, comprising:
module M1: scanning by a drawing robot, and collecting environmental data;
module M2: constructing a map according to the collected environmental data;
module M3: judging the definition of the map, and carrying out map repairing and point position taking according to the definition;
module M4: and (4) carrying out elevator control and telephone system installation, and carrying out test and operation training.
7. The robot rapid, efficient and low-cost deployment system of claim 6, wherein the building is scanned layer by remote control, data collected by the lidar and the inertial sensor mounted on the mapping robot are encoded by the encoder, a data packet is generated and uploaded to the server according to a preset format.
8. The robot rapid, efficient and low-cost deployment system of claim 7, wherein the corresponding data packet is read in the server, the laser data and the odometer data at the current moment are obtained, the laser matching is performed by using the odometer value as an initial value to obtain a calibrated position, then a raster map is generated by using the laser data, constraints are generated between each frame and each sensor, and loop optimization is performed according to a preset frequency;
and (4) repairing the map according to the uploaded pictures and the description information, and storing the map in a map server after finishing repairing the map on all floors.
9. The robot rapid, efficient and low-cost deployment system according to claim 6, characterized in that whether room points need to be collected is judged according to the actual situation of a map, and if the definition of the outline of a room door is within a preset range, the points are directly taken and stored to a server; and if the definition of the outline of the room door exceeds the preset range, re-taking the point location and building the icon point.
10. The system of claim 9, wherein after the construction of the landmark points is completed, the map and the room points are downloaded from the server, and the elevator points, the avoidance points, and the waiting points are automatically checked by a preset program to perform a secondary check on the room points.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104991463A (en) * | 2015-05-21 | 2015-10-21 | 北京云迹科技有限公司 | Robot semi-autonomous mapping method and system |
| US20190168386A1 (en) * | 2016-05-19 | 2019-06-06 | Ecovacs Robotics Co., Ltd. | Self-moving robot, map building method, and map invoking method for combined robot |
| US20190219700A1 (en) * | 2017-11-17 | 2019-07-18 | DeepMap Inc. | Iterative closest point process based on lidar with integrated motion estimation for high definition maps |
| KR102194426B1 (en) * | 2020-04-29 | 2020-12-24 | 주식회사 트위니 | Apparatus and method for environment recognition of indoor moving robot in a elevator and recording medium storing program for executing the same, and computer program stored in recording medium for executing the same |
| CN112318500A (en) * | 2020-10-19 | 2021-02-05 | 武汉理工大学 | High-precision book grabbing method based on library dynamic space foundation |
| CN112729321A (en) * | 2020-12-28 | 2021-04-30 | 上海有个机器人有限公司 | Robot map scanning method and device, storage medium and robot |
| CN112923927A (en) * | 2021-01-28 | 2021-06-08 | 上海有个机器人有限公司 | Robot scanning map processing method, device, terminal and storage medium |
| CN113111144A (en) * | 2021-04-14 | 2021-07-13 | 北京云迹科技有限公司 | Room marking method and device and robot movement method |
| US20230039466A1 (en) * | 2020-02-10 | 2023-02-09 | Metralabs Gmbh Neue Technologien Und Systeme | Method and a system for conveying a robot in an elevator |
-
2021
- 2021-09-27 CN CN202111148484.0A patent/CN113848918A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104991463A (en) * | 2015-05-21 | 2015-10-21 | 北京云迹科技有限公司 | Robot semi-autonomous mapping method and system |
| US20190168386A1 (en) * | 2016-05-19 | 2019-06-06 | Ecovacs Robotics Co., Ltd. | Self-moving robot, map building method, and map invoking method for combined robot |
| US20190219700A1 (en) * | 2017-11-17 | 2019-07-18 | DeepMap Inc. | Iterative closest point process based on lidar with integrated motion estimation for high definition maps |
| US20230039466A1 (en) * | 2020-02-10 | 2023-02-09 | Metralabs Gmbh Neue Technologien Und Systeme | Method and a system for conveying a robot in an elevator |
| KR102194426B1 (en) * | 2020-04-29 | 2020-12-24 | 주식회사 트위니 | Apparatus and method for environment recognition of indoor moving robot in a elevator and recording medium storing program for executing the same, and computer program stored in recording medium for executing the same |
| CN112318500A (en) * | 2020-10-19 | 2021-02-05 | 武汉理工大学 | High-precision book grabbing method based on library dynamic space foundation |
| CN112729321A (en) * | 2020-12-28 | 2021-04-30 | 上海有个机器人有限公司 | Robot map scanning method and device, storage medium and robot |
| CN112923927A (en) * | 2021-01-28 | 2021-06-08 | 上海有个机器人有限公司 | Robot scanning map processing method, device, terminal and storage medium |
| CN113111144A (en) * | 2021-04-14 | 2021-07-13 | 北京云迹科技有限公司 | Room marking method and device and robot movement method |
Non-Patent Citations (2)
| Title |
|---|
| 孙嘉;彭雨馨;胡媛;崔文媛;: "区域型智能快递"车"设计", 电子测试, no. 06 * |
| 孙嘉;彭雨馨;胡媛;崔文媛;: "区域型智能快递"车"设计", 电子测试, no. 06, 15 March 2020 (2020-03-15) * |
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