CN112947440A - Charging seat searching method for automatic charging of robot - Google Patents
Charging seat searching method for automatic charging of robot Download PDFInfo
- Publication number
- CN112947440A CN112947440A CN202110164714.6A CN202110164714A CN112947440A CN 112947440 A CN112947440 A CN 112947440A CN 202110164714 A CN202110164714 A CN 202110164714A CN 112947440 A CN112947440 A CN 112947440A
- Authority
- CN
- China
- Prior art keywords
- charging seat
- robot
- laser radar
- charging
- radar data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 21
- 230000011218 segmentation Effects 0.000 claims description 12
- 230000000630 rising effect Effects 0.000 claims description 5
- 238000013499 data model Methods 0.000 claims description 3
- 238000001914 filtration Methods 0.000 claims description 3
- 238000012886 linear function Methods 0.000 claims description 3
- 230000003044 adaptive effect Effects 0.000 claims description 2
- 238000005516 engineering process Methods 0.000 description 2
- 210000001503 joint Anatomy 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000007599 discharging Methods 0.000 description 1
- 238000003032 molecular docking Methods 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 238000010408 sweeping Methods 0.000 description 1
Images
Classifications
-
- 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
-
- 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
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0221—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving a learning process
-
- 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
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
- G05D1/0225—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory involving docking at a fixed facility, e.g. base station or loading bay
Abstract
The invention discloses a charging seat searching method for automatic charging of a robot, which comprises the following steps: initially searching for charging seat characteristics; calculating the initial position of a charging seat, judging the distance between the robot and the position of the charging seat, and directly and accurately searching the position of the charging seat if the position of the charging seat of the robot is close to the position of the robot; if the position of the robot charging seat is far away from the position of the robot, the robot is controlled to run to a charging reference point in front of the charging seat, and after the robot is judged to reach the reference point, the position of the charging seat is accurately searched. The robot of the invention initially searches the characteristics of the charging seat and accurately searches the position of the charging seat by detecting the charging seat through the laser radar, firstly determines the position range of the charging seat, further determines the position relation of the charging seat relative to the robot, and calculates the specific direction of the robot in front of the charging seat, so that the robot moves to the right front of the front panel of the charging seat and then realizes butt charging, thereby improving the positioning accuracy of the robot and the searching efficiency of the charging seat.
Description
Technical Field
The invention relates to the technical field of robot wireless charging, in particular to a charging seat searching method for robot automatic charging.
Background
In recent years, with the continuous development of computer intelligent control technology and sensor technology, service robots are more and more widely applied to the lives of people, such as floor sweeping robots, market shopping guide robots, catering service robots and the like. Since service robots in the market are basically powered by batteries, when the power of the robot is exhausted, people are required to move the robot to a charging place for charging. The manual intervention charging mode not only wastes manpower time, but also causes the working time of the robot to be limited, and reduces the autonomy and the intellectualization of the robot.
The robot in the prior art generally uses detection infrared signals to realize that the robot automatically connects to a charging seat for charging, and the charging method needs to install at least 2 infrared transmitting tubes on the charging seat, and correspondingly needs to install an infrared receiving sensor on the robot. According to the charging and discharging method, the robot needs to be provided with an additional structural design and a plurality of sensors are mounted, so that the docking precision is not high. When the robot does not detect the specific position of the charging seat, the robot may search unintentionally and is time-consuming.
Disclosure of Invention
The invention aims to provide a charging seat searching method for automatic charging of a robot, which aims to solve the problem that the butt joint precision of the robot and the charging seat is not high in the prior art.
In order to achieve the above object, the present invention provides a method for searching a charging stand for automatically charging a robot, wherein the robot has a chassis capable of rotating 360 degrees, a lidar is fixedly mounted on the chassis, and the lidar emits a laser beam to detect an obstacle in the surrounding environment to obtain lidar data related to the obstacle; a left groove and a right groove which are recessed inwards are formed in a front panel of the charging seat, the left groove and the right groove are symmetrically arranged on two sides of the charging seat, the heights of the left groove and the right groove are both flush with the scanning height of the laser radar, and the left groove, the right groove and a middle panel positioned between the left groove and the right groove form the characteristics of the charging seat together; the charging seat searching method comprises the following steps:
s1, primarily searching the charging seat characteristics, judging whether the robot searches the charging seat characteristics, and executing the step S2 if the robot searches the charging seat characteristics; if the robot does not search the charging seat characteristics, controlling the chassis of the robot to rotate for a certain angle and then searching the charging seat characteristics again;
s2, calculating the initial position of the charging seat, judging the distance between the robot and the position of the charging seat, and if the position of the charging seat of the robot is close to the position of the robot, directly and accurately searching the position of the charging seat; and if the position of the robot charging seat is far away from the position of the robot, controlling the robot to run to a charging reference point C in front of the charging seat, and accurately searching the position of the charging seat after judging that the robot reaches the reference point C.
Further, the algorithm for initially searching the charging dock characteristic in step S1 is specifically as follows:
1.1, reading a frame of laser radar Data, and storing all scanned laser radar Data points into a laser point Data array, wherein the Data of the laser radar Data points comprises a scanning distance and a scanning angle;
1.2, firstly, confirming a segmentation threshold value by using an adaptive variable threshold segmentation method, and defining a segmentation threshold value linear function Div ═ f (D) to determine the segmentation threshold values of different laser radar data points; then two adjacent laser radar data points L are calculatedaAnd LbIf Δ d is equal to Δ d>Div, then the two lidar data points LaAnd LbAre different areas; finally, one frame of laser radar data is divided into N blocks, and the divided blocks are represented as RiEach block includes GiA point, i 1, 2.... N;
1.3 traversing the partitioned block RiIf the number of the laser radar data points in a certain block is less than 3, the block is considered as a noise point, and the block is discarded; then detecting whether the laser radar data points in the block conform to the characteristics of the charging seat data points, traversing all the laser radar data points in the block, and calculating two adjacent laser radar data points LaAnd LbWhether the slot depth superposition error threshold of the charging seat is met or not is judged, the number M of the matched laser radar data points is calculated, and the number of the laser radar data points of the block is NaThe matching ratio P is M/Na；
1.4 for all the divided blocks RiSorting according to the matching rate from top to bottom, setting the block with the highest matching rate as the position of the charging seat, and calculating the linear length of the block according to the cosine theorem and the head and tail laser radar data points of the block
Wherein l1Scanning distance for the left lidar data point of the block, l2Scanning distance of the right laser radar data point of the block, and theta is an angle difference between the left laser radar data point and the right laser radar data point; checking whether the length of the block accords with a charging seat block set value superposition error value or not, and circularly calculating the straight line length of the block until a charging seat block which simultaneously meets the block checking length and has the highest matching rate is found;
1.5, calculating the coordinate P of the central point of the block where the charging seat is positionedaAccording to PaThe coordinate finally obtains the relative distance D between the charging seat and the robotcAnd azimuth Da。
Further, the algorithm for precisely searching the charging seat position in step S2 is as follows:
2.1, reading a frame of laser radar Data, and storing all scanned laser radar Data points into a laser point Data array, wherein the Data of the laser radar Data points comprises a scanning distance and a scanning angle;
2.2, setting a near-range scanning parameter value, traversing laser radar Data points in the laser point Data array, and filtering invalid Data and laser radar Data points which exceed a scanning range;
2.3, traversing the filtered laser point Data array, calculating a difference value delta d between the two points, finding out continuous laser radar Data points which are consistent with a laser Data model of the charging seat from the laser point Data array according to the characteristics of the charging seat when the delta d exceeds a linear characteristic threshold value, positioning rising edge Data points and falling edge Data points of the characteristics of the charging seat, and finally obtaining a left characteristic point and a right characteristic point of a middle panel of the charging seat; the complete charging seat characteristic sequentially comprises a left panel, a left falling edge, a left groove, a left rising edge, a middle panel, a right falling edge, a right groove, a right rising edge and a right panel from left to right;
2.4, judging whether the robot is positioned on the left side or the right side of a vertical central line of the charging seat according to the left characteristic point and the right characteristic point data of the charging seat, and when the length of the line segment PL is greater than that of the line segment PR, the robot is positioned on the right side of the central line of the charging seat, otherwise, the robot is positioned on the left side; knowing the angle of LPR and the lengths of line segment PL and line segment PR, calculating the angle of POV according to the cosine theorem and a trigonometric function, judging whether the robot is in a direct butt-joint charging area, when the angle of POV is less than 20 degrees, the robot can directly start to retreat and butt-joint a charging seat, and when the angle of POV is more than or equal to 20 degrees, firstly controlling the robot to run to a charging reference point C;
and 2.5, if the robot is not in the direct butt-joint charging area, the coordinate of the point of the robot is P (x, y), the running direction of the robot is a vector PC, the angle of the vector PC in a laser radar coordinate system and the length of a model | PC | are calculated, the angle of the vector PC in the laser radar coordinate system is converted into an angle β in a mileage coordinate system, the robot rotates the angle β first and then advances by the distance | PC | to reach a charging reference point C.
Compared with the prior art, the invention has the following beneficial effects:
the invention relates to a charging seat searching method for robot automatic charging, wherein a robot transmits a laser beam through a laser radar to preliminarily search the characteristics of a charging seat and accurately search the position of the charging seat, the position range of the charging seat is firstly determined, the position relation of the charging seat relative to the robot is further determined, and the specific direction of the robot in front of the charging seat is specifically calculated, so that the robot moves to the position right in front of the front panel of the charging seat and then realizes butt charging, thereby improving the positioning accuracy of the robot and the searching efficiency of the charging seat.
In addition to the objects, features and advantages described above, other objects, features and advantages of the present invention are also provided. The present invention will be described in further detail below with reference to the drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a geometric diagram illustrating the matching of a charging seat and a robot in a charging seat searching method for automatically charging the robot according to the present invention;
FIG. 2 is a flowchart of a charging seat searching method of a robot according to the present invention.
Detailed Description
Embodiments of the invention will be described in detail below with reference to the drawings, but the invention can be implemented in many different ways, which are defined and covered by the claims.
Referring to fig. 1 and 2, in an embodiment of the invention, a robot has a chassis capable of rotating 360 degrees, a laser radar is fixedly mounted on the chassis, a rotating laser head of the laser radar rotates 360 degrees, and the laser radar emits a laser beam to detect an obstacle in a surrounding environment, so as to obtain laser radar data related to the obstacle. Set up the left recess 1.1 and the right recess 1.2 of inside concave yield on charging seat 1's the front panel, left recess and right recess symmetry set up the both sides at the charging seat, and the high parallel and level setting of scanning height that all with laser radar of left recess and right recess, and left recess, right recess and the middle panel 1.3 that is located between left recess and the right recess form the charging seat characteristic jointly. The charging seat searching method of the robot comprises the following steps:
s1, primarily searching the charging seat characteristics, judging whether the robot searches the charging seat characteristics, and executing the step S2 if the robot searches the charging seat characteristics; if the robot does not search the charging seat characteristics, controlling the chassis of the robot to rotate by 20 degrees and then searching the charging seat characteristics again; the algorithm for searching the charging seat characteristics in the step is specifically as follows:
1.1, reading a frame of laser radar Data, and storing all scanned laser radar Data points into a laser radar Data point Data array, wherein the Data of the laser radar Data points comprises a scanning distance and a scanning angle.
1.2, for each frame of laser radar data, dividing the laser radar data points into different blocks according to a division threshold; if the distance between two continuous laser radar data points is smaller than a threshold value, the two laser radar data points belong to the same partition block; if the distance between two consecutive lidar data points is greater than a threshold, the data frame is divided from the two lidar data points; the distribution of the laser radar data points is not uniform, firstly, a self-adaptive variable threshold segmentation method is used for confirming segmentation threshold values, and a segmentation threshold value linear function Div ═ f (D) is defined to confirm the segmentation threshold values of different laser radar data points; then two adjacent laser radar data points L are calculatedaAnd LbIf Δ d is equal to Δ d>Div, then the two lidar data points LaAnd LbAre different areas; finally, one frame of laser radar data is divided into N blocks, and the divided blocks are represented as RiEach block includes GiA point, i 1, 2.
1.3 traversing the partitioned block RiIf the number of the laser radar data points in a certain block is less than 3, the block is considered as a noise point, and the block is discarded; then detecting whether the laser radar data points in the block conform to the characteristics of the charging seat data points, traversing all the laser radar data points in the block, and calculating two adjacent laser radar data points LaAnd LbWhether the slot depth superposition error threshold of the charging seat is met or not is judged, the number M of the matched laser radar data points is calculated, and the number of the laser radar data points of the block is NaThe matching ratio P is M/Na。
1.4 for all the divided blocks RiSorting according to the matching rate from top to bottom, setting the block with the highest matching rate as the position of the charging seat, and calculating the linear length of the block according to the cosine theorem and the head and tail laser radar data points of the block
Wherein l1Scanning distance for the left lidar data point of the block, l2Scanning distance of the right laser radar data point of the block, and theta is an angle difference between the left laser radar data point and the right laser radar data point; and checking whether the length of the block accords with the superposition error of the set value of the charging seat block, and circularly calculating the linear length of the block until the charging seat block which simultaneously meets the block checking length and has the highest matching rate is found.
1.5, calculating the coordinate P of the central point of the block where the charging seat is positionedaAccording to PaThe coordinate finally obtains the relative distance D between the charging seat and the robotcAnd azimuth Da。
S2, calculating the initial position of the charging seat, judging the distance between the robot and the position of the charging seat 1, and if the position of the charging seat of the robot is close to the position of the robot, directly and accurately searching the position of the charging seat; if the position of the robot charging seat is far away from the position of the robot, the robot is controlled to run to a charging reference point in front of the charging seat, and after the robot is judged to reach the reference point, the position of the charging seat is accurately searched. The algorithm for accurately searching the position of the charging seat in the step is as follows:
and 2.1, reading a frame of laser radar Data, and storing all scanned laser radar Data points into a laser point Data array, wherein the Data of the laser radar Data points comprises a scanning distance and a scanning angle.
And 2.2, setting a near-distance scanning parameter value, traversing the laser radar Data points in the laser point Data array, and filtering invalid Data and laser radar Data points which exceed the scanning range.
2.3, traversing the filtered laser point Data array, calculating a difference value delta d between the two points, finding out continuous laser radar Data points which are consistent with a laser Data model of the charging seat from the laser point Data array according to the characteristics of the charging seat when the delta d exceeds a linear characteristic threshold value, positioning rising edge Data points and falling edge Data points of the characteristics of the charging seat, and finally obtaining a left characteristic point and a right characteristic point of a middle panel of the charging seat; a complete charging seat feature comprises a left panel 1.4, a left concave edge 1.5, a left concave inner wall plate, a left return edge 1.6, a middle panel 1.3, a right concave edge 1.7, a right concave inner wall plate, a right return edge 1.8 and a right panel 1.9 in sequence from left to right.
2.4, judging whether the robot is positioned on the left side or the right side of a vertical central line of the charging seat according to the left characteristic point and the right characteristic point data of the charging seat, and when the length of the line segment PL is greater than that of the line segment PR, the robot is positioned on the right side of the central line of the charging seat, otherwise, the robot is positioned on the left side; knowing the angle α between line segments PL and PR1And the length of the line segment PL and the line segment PR, and calculating the included angle alpha between the line segment PO and the line segment OV according to the cosine theorem and the trigonometric function2Firstly, judging whether the robot is in a direct butt-joint charging area, and when alpha is reached2When the angle is less than 20 degrees, the robot can directly start to retreat to be in butt joint with the charging seat, and when the angle is alpha2When the temperature is more than or equal to 20 ℃, the robot is controlled to move to a charging reference point C; p is the central point of the chassis of the robot, L is the left characteristic point of the charging seat, and R is the right characteristic point of the charging seat. The intersection line of the left groove 1.1 and the middle panel 1.3 is a left characteristic line, the left characteristic point L is the intersection point of the laser beam emitted by the laser radar and the left characteristic line, the intersection line of the right groove 1.2 and the middle panel 1.3 is a right characteristic line, and the right characteristic point R is the intersection point of the laser beam emitted by the laser radar and the right characteristic line.
And 2.5, if the robot is not in the direct butt-joint charging area, the coordinate of the point of the robot is P (x, y), the running direction of the robot is a vector PC, the angle of the vector PC in a laser radar coordinate system and the length of a model | PC | are calculated, the angle of the vector PC in the laser radar coordinate system is converted into an angle β in a mileage coordinate system, the robot rotates the angle β first and then advances by the distance | PC | to reach a charging reference point C.
Therefore, the position relation of the charging seat relative to the robot is accurately determined by the method; then the robot is automatically connected with the charging seat on the basis, and finally the automatic charging of the robot is realized.
In the invention, if the accumulated rotation of the chassis of the robot is controlled to exceed 360 degrees and the characteristics of the charging seat are not searched, the searching work is finished.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (3)
1. A charging seat searching method for robot automatic charging is characterized in that the robot is provided with a chassis capable of rotating 360 degrees, a laser radar is fixedly arranged on the chassis, and the laser radar emits laser beams to detect obstacles in the surrounding environment so as to obtain laser radar data related to the obstacles; a left groove (1.1) and a right groove (1.2) which are recessed inwards are formed in a front panel of the charging seat (1), the left groove and the right groove are symmetrically arranged on two sides of the charging seat, the heights of the left groove and the right groove are both parallel to the scanning height of the laser radar, and the left groove, the right groove and a middle panel (1.3) positioned between the left groove and the right groove jointly form the characteristics of the charging seat; the charging seat searching method comprises the following steps:
s1, primarily searching the charging seat characteristics, judging whether the robot searches the charging seat characteristics, and executing the step S2 if the robot searches the charging seat characteristics; if the robot does not search the charging seat characteristics, controlling the chassis of the robot to rotate for a certain angle and then searching the charging seat characteristics again;
s2, calculating the initial position of the charging seat, judging the distance between the robot and the charging seat (1), and if the charging seat of the robot is close to the position of the robot, directly and accurately searching the position of the charging seat; and if the position of the robot charging seat is far away from the position of the robot, controlling the robot to run to a charging reference point C in front of the charging seat, and accurately searching the position of the charging seat after judging that the robot reaches the reference point C.
2. The cradle searching method of claim 1, wherein the algorithm for preliminary searching the cradle characteristics in step S1 is as follows:
1.1, reading a frame of laser radar Data, and storing all scanned laser radar Data points into a laser radar Data point Data array, wherein the Data of the laser radar Data points comprises a scanning distance and a scanning angle;
1.2, firstly, confirming a segmentation threshold value by using an adaptive variable threshold segmentation method, and defining a segmentation threshold value linear function Div ═ f (D) to determine the segmentation threshold values of different laser radar data points; then two adjacent laser radar data points L are calculatedaAnd LbIf Δ d is equal to Δ d>Div, then the two lidar data points LaAnd LbAre different areas; finally, one frame of laser radar data is divided into N blocks, and the divided blocks are represented as RiEach block includes GiA point, i 1, 2.... N;
1.3 traversing the partitioned block RiIf the number of the laser radar data points in a certain block is less than 3, the block is considered as a noise point, and the block is discarded; then detecting whether the laser radar data points in the block conform to the characteristics of the charging seat data points, traversing all the laser radar data points in the block, and calculating two adjacent laser radar data points LaAnd LbWhether the slot depth superposition error threshold of the charging seat is met or not is judged, the number M of the matched laser radar data points is calculated, and the number of the laser radar data points of the block is NaThe matching ratio P is M/Na；
1.4 for all the divided blocks RiSorting according to the matching rate from top to bottom, setting the block with the highest matching rate as the position of the charging seat, and calculating according to the cosine theorem and the head and tail laser radar data points of the blockCalculating the linear length of the block
Wherein l1Scanning distance for the left lidar data point of the block, l2Scanning distance of the right laser radar data point of the block, and theta is an angle difference between the left laser radar data point and the right laser radar data point; checking whether the length of the block accords with a charging seat block set value superposition error value or not, and circularly calculating the straight line length of the block until a charging seat block which simultaneously meets the block checking length and has the highest matching rate is found;
1.5, calculating the coordinate P of the central point of the block where the charging seat is positionedaAccording to PaThe coordinate finally obtains the relative distance D between the charging seat and the robotcAnd azimuth Da。
3. The cradle searching method of claim 1, wherein the algorithm for searching the cradle position precisely in step S2 is as follows:
2.1, reading a frame of laser radar Data, and storing all scanned laser radar Data points into a laser radar Data point Data array, wherein the Data of the laser radar Data points comprises a scanning distance and a scanning angle;
2.2, setting a near-range scanning parameter value, traversing laser radar Data points in a laser radar Data point Data array, and filtering invalid Data and laser radar Data points which exceed a scanning range;
2.3, traversing the filtered laser radar Data point Data array, calculating a difference value delta d between the two points, finding out continuous laser radar Data points which are consistent with a laser Data model of a charging seat from the laser radar Data point Data array according to the characteristics of the charging seat when the delta d exceeds a linear characteristic threshold value, positioning rising edge Data points and falling edge Data points of the characteristics of the charging seat, and finally obtaining a left characteristic point and a right characteristic point of a middle panel of the charging seat; the complete charging seat is characterized by sequentially comprising a left panel (1.4), a left inner concave edge (1.5), a left groove inner wall plate, a left return edge (1.6), a middle panel (1.3), a right inner concave edge (1.7), a right groove inner wall plate, a right return edge (1.8) and a right panel (1.9) from left to right;
2.4, judging whether the robot is positioned on the left side or the right side of a vertical central line of the charging seat according to the left characteristic point and the right characteristic point data of the charging seat, and when the length of the line segment PL is greater than that of the line segment PR, the robot is positioned on the right side of the central line of the charging seat, otherwise, the robot is positioned on the left side; knowing the angle of the LPR and the lengths of the line segment PL and the line segment PR, calculating the angle of the POV according to the cosine theorem and a trigonometric function, judging whether the robot is in a direct butt-joint charging area, when the POV is less than 20 degrees, directly starting retreating the robot to butt-joint the charging seat, and when the POV is more than or equal to 20 degrees, firstly controlling the robot to run to a charging reference point C;
and 2.5, if the robot is not in the direct butt-joint charging area, the coordinate of the point of the robot is P (x, y), the running direction of the robot is a vector PC, the angle of the vector PC in a laser radar coordinate system and the length of a model | PC | are calculated, the angle of the vector PC in the laser radar coordinate system is converted into an angle β in a mileage coordinate system, the robot rotates the angle β first and then advances by the distance | PC | to reach a charging reference point C.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110164714.6A CN112947440A (en) | 2021-02-06 | 2021-02-06 | Charging seat searching method for automatic charging of robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110164714.6A CN112947440A (en) | 2021-02-06 | 2021-02-06 | Charging seat searching method for automatic charging of robot |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112947440A true CN112947440A (en) | 2021-06-11 |
Family
ID=76242910
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110164714.6A Pending CN112947440A (en) | 2021-02-06 | 2021-02-06 | Charging seat searching method for automatic charging of robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112947440A (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115933706A (en) * | 2023-02-07 | 2023-04-07 | 科大讯飞股份有限公司 | Robot charging method and device, robot and robot system |
| CN116009561A (en) * | 2023-03-24 | 2023-04-25 | 科大讯飞股份有限公司 | Robot and pile searching method and device thereof and storage medium |
| CN116678353A (en) * | 2023-08-02 | 2023-09-01 | 国网天津市电力公司滨海供电分公司 | Method and system for testing operation range of charging robot connected with vehicle interface |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104635730A (en) * | 2013-11-13 | 2015-05-20 | 沈阳新松机器人自动化股份有限公司 | Automatic charging method for robot |
| CN109755995A (en) * | 2018-12-14 | 2019-05-14 | 华南理工大学 | Robot automatic charging interconnection method based on ROS robot operating system |
| US20200150676A1 (en) * | 2018-11-09 | 2020-05-14 | Shenzhen Silver Star Intelligent Technology Co., Ltd | Method, device for automatically charging robot, charging station and robot |
| US20200241551A1 (en) * | 2019-01-28 | 2020-07-30 | Fetch Robotics, Inc. | System and Method for Semantically Identifying One or More of an Object and a Location in a Robotic Environment |
| US20200256957A1 (en) * | 2017-10-30 | 2020-08-13 | Denso Corporation | Laser radar device |
-
2021
- 2021-02-06 CN CN202110164714.6A patent/CN112947440A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104635730A (en) * | 2013-11-13 | 2015-05-20 | 沈阳新松机器人自动化股份有限公司 | Automatic charging method for robot |
| US20200256957A1 (en) * | 2017-10-30 | 2020-08-13 | Denso Corporation | Laser radar device |
| US20200150676A1 (en) * | 2018-11-09 | 2020-05-14 | Shenzhen Silver Star Intelligent Technology Co., Ltd | Method, device for automatically charging robot, charging station and robot |
| CN109755995A (en) * | 2018-12-14 | 2019-05-14 | 华南理工大学 | Robot automatic charging interconnection method based on ROS robot operating system |
| US20200241551A1 (en) * | 2019-01-28 | 2020-07-30 | Fetch Robotics, Inc. | System and Method for Semantically Identifying One or More of an Object and a Location in a Robotic Environment |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115933706A (en) * | 2023-02-07 | 2023-04-07 | 科大讯飞股份有限公司 | Robot charging method and device, robot and robot system |
| CN116009561A (en) * | 2023-03-24 | 2023-04-25 | 科大讯飞股份有限公司 | Robot and pile searching method and device thereof and storage medium |
| CN116678353A (en) * | 2023-08-02 | 2023-09-01 | 国网天津市电力公司滨海供电分公司 | Method and system for testing operation range of charging robot connected with vehicle interface |
| CN116678353B (en) * | 2023-08-02 | 2023-10-13 | 国网天津市电力公司滨海供电分公司 | Method and system for testing operation range of charging robot connected with vehicle interface |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112947440A (en) | Charging seat searching method for automatic charging of robot | |
| CN112947441B (en) | Control method for automatic docking and charging of robot and charging seat | |
| CN109885049B (en) | Automatic mapping and path matching method for laser-guided AGV (automatic guided vehicle) based on dead reckoning | |
| CN108007452B (en) | Method and device for updating environment map according to obstacle and robot | |
| CN111693050B (en) | Indoor medium and large robot navigation method based on building information model | |
| US20140081531A1 (en) | Positioning system using radio frequency signals | |
| TWI604980B (en) | Vehicle control system and vehicle control method | |
| CN113587930B (en) | Indoor and outdoor navigation method and device of autonomous mobile robot based on multi-sensor fusion | |
| CN113359769B (en) | Indoor autonomous mobile robot composite navigation method and device | |
| CN111090087A (en) | Intelligent navigation machine, laser radar blind area compensation method and storage medium | |
| CN112928799A (en) | Automatic butt-joint charging method of mobile robot based on laser measurement | |
| CN110907891A (en) | AGV positioning method and device | |
| CN108536146B (en) | Intelligent control method for positioning charging base of mobile robot based on path and RSSI (received Signal Strength indicator) | |
| CN114355889A (en) | Control method, robot charging stand, and computer-readable storage medium | |
| CN113607166B (en) | Indoor and outdoor positioning method and device for autonomous mobile robot based on multi-sensor fusion | |
| CN113030997B (en) | Method for detecting travelable area of open-pit mine area based on laser radar | |
| CN110928296B (en) | Method for avoiding charging seat by robot and robot thereof | |
| CN113490973B (en) | Information processing device and mobile robot | |
| CN116339326A (en) | Autonomous charging positioning method and system based on stereoscopic camera | |
| Yang et al. | Towards high accuracy parking slot detection for automated valet parking system | |
| CN114489050A (en) | Obstacle avoidance route control method, device, equipment and storage medium for straight line driving | |
| CN114228411A (en) | Connection control method, device, equipment and storage medium | |
| CN113805581B (en) | Method for docking excavator and mine card and main control device | |
| CN113138594A (en) | Automatic driving method and device | |
| CN114179092B (en) | Vehicle carrying control method, device, equipment and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |