CN108762261B - Mobile robot traversal path planning method based on double wireless networks - Google Patents
Mobile robot traversal path planning method based on double wireless networks Download PDFInfo
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Abstract
The mobile robot comprises a driving wheel, a driving motor connected with the driving wheel, a charging electrode male end arranged at the front end of the mobile robot and a master control electronic device, a charging base comprises a charging electrode female end, a power jack and a charging control electronic device, the charging control electronic device is provided with a controller and a first WIFI module connected with the controller, the master control electronic device is provided with a processor and a second WIFI module connected with the processor, the mobile robot further comprises an auxiliary network device and a third WIFI module, and the processor is provided with a linked list L = { (a) }i,bi) Carry out environment map storage, wherein ai=RⅠ i，bi=RⅡ iAnd a traversal path planning method arranged in the processor, the traversal path planning method comprising: and walking from left to right and then from right to left along the wireless signal intensity contour line, judging whether the obstacle is a boundary according to the environment map when the obstacle is encountered, carrying out corresponding processing, and finally carrying out ending condition judgment.
Description
Technical Field
The invention relates to a mobile robot traversal path planning method based on double wireless networks, and belongs to the field of mobile robots.
Background
Mobile robots have begun to be used in our lives, such as dust collection robots and mowing robots, and the application of robots reduces daily labor burden to some extent, which is a trend of future technology development.
At present, the development of mobile robot technology is not perfect, for example, dust collection robots and mowing robots are not efficient due to lack of positioning means and no environment map building. When the robot works, a random path is adopted, the robot walks randomly in a working environment, and no path planning is needed. When the work is finished or the electric quantity is insufficient, a method for searching along the boundary of a work area is often adopted for searching the charging base, for example, a dust collection robot can search the charging base along the wall, and the charging base is arranged close to the wall; the mowing robot works on the lawn, the alternating current cable is laid around the lawn, and the charging base is arranged on the cable, so that the mowing robot can find the charging base along the cable. In this way, under the condition of complex environment or large area, it takes a long time to return to the charging base under average conditions, and it is likely that the charging base is nearby and the mobile robot needs to search from the reverse direction. In addition, there are also ways of random collection, such as some vacuum robots, which are inefficient and often fail.
With the development of technology, mobile robots are beginning to assemble two-dimensional or even three-dimensional laser radar for environment detection and map building, but the cost of the method is very high, and the price of the sensor per se is far higher than that of the current mobile robots. The image sensor is also adopted for environment detection and map building, and the method has high requirements on hardware computing capacity and harsh requirements on environment illumination conditions.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, position marking is carried out by adopting two groups of intensity information of large-scale wireless signals, traversal path planning is carried out according to an environment map established in the early stage, and the working efficiency is greatly improved on the premise of not increasing the hardware cost.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a mobile robot traversal path planning method based on double wireless networks is provided, the mobile robot comprises a driving wheel, a driving motor connected with the driving wheel and a charging electrode male end arranged at the front end of the mobile robot, a master control electronic device is arranged in the mobile robot, the master control electronic device comprises a processor for performing centralized control, a motor driving circuit connected with the processor, the motor driving circuit is connected with the driving motor, an obstacle detection circuit connected with the processor is used for performing obstacle avoidance and path planning, an inertial navigation system connected with the processor is used for calculating the position (x, y) and the direction theta of the mobile robot, and the mobile robot traversal path planning method further comprises a charging circuit connected with the processor, and the charging circuit is connected with the charging electrode male end, the output of the charging circuit is connected with a rechargeable battery, the output of the rechargeable battery is connected with a second power supply circuit, and the second power supply circuit provides power for subsequent circuitsA source; the charging base comprises a charging electrode female end, a power jack and a charging control electronic device, wherein the charging control electronic device is provided with a controller for performing centralized control, a first power circuit and a filter circuit which are connected with the power jack, and a switching tube which is connected with the filter circuit, is controlled by the controller, outputs and is connected with a current detection circuit, the current detection circuit is connected with the charging electrode female end, converts a current signal into a voltage signal and sends the voltage signal to the controller, the charging control electronic device is provided with a first WIFI module which is connected with the controller, and the first WIFI module is set to be in an AP mode; the charging base is provided with a first WIFI module, the first WIFI module is set to be in an AP mode, and the charging base is arranged at a position different from the position of the charging base; the main control electronic device is provided with a third WIFI module connected with the processor, the third WIFI module is set to be in an STA mode, the processor acquires a wireless signal strength value RSSI received by the third WIFI module, the RSSI is recorded as R, and the wireless signal strength value R is specifically received by the first WIFI moduleⅠAnd the wireless signal intensity value R of the second WIFI moduleⅡ(ii) a The processor setting linked list L = { (a)i,bi) In which a isi=RⅠ i，bi=RⅡ iI =0,1,2,3Ⅰ iAnd RⅡ iThe wireless signal strength values of the first WIFI module and the second WIFI module at the equidistant positions of the working environment boundary are obtained; and a traversal path planning method arranged in the processor, the traversal path planning method comprising the following steps:
(1) the processor is internally provided with an array A = { A [0]],A[1]In which A [ j ]]=RⅠ jJ =0,1, wherein RⅠ jRepresenting a wireless signal strength value of the first WIFI module stored by the mobile robot; the mobile robot leaves the charging base to store the current wireless signalIntensity value A [0]]=RⅠ；
(2) The mobile robot rotates leftwards and walks along the boundary, the translation distance s from the mobile robot to the charging base is calculated by adopting a center distance calculation algorithm, and when the translation distance s is reached>When W, then store the current wireless signal intensity value A [0]]=RⅠEntering step 3, wherein W is the width of the vehicle body of the mobile robot; if the wireless signal strength value RⅠ>A[0]Entering step 8;
(3) the mobile robot enters a leftward tracking process, and the tracking path is wireless signal intensity RⅠThe contour of (A), i.e. the radio signal strength is A0]A path of (a); when the mobile robot detects an obstacle, reading the current wireless signal intensity value RⅠAnd RⅡJudging the obstacle type according to the obstacle distinguishing algorithm, if the obstacle is the obstacle, storing the wireless signal intensity value A [1 ]]=RⅠWalk along the obstacle on the left side, when | RⅠ-A[1]|>Then, entering step 4; if the boundary is detected, entering step 5;
(4) the mobile robot walks along the obstacle on the left side when the absolute value of R isⅠ-A[1]|<Returning to the step 3;
(5) the mobile robot rotates rightwards and walks along the wall at the right side, the center distance calculation algorithm is adopted to calculate the distance between the mobile robot and the charging base, and when the distance is s, the mobile robot moves away>When W, then store the current wireless signal intensity value A [0]]=RⅠEntering step 6; if the wireless signal strength value RⅠ>A[0]Entering step 8;
(6) the mobile robot enters a rightward tracking process, and the tracking path is the wireless signal intensity RⅠThe contour of (A), i.e. the radio signal strength is A0]A path of (a); when the mobile robot meets an obstacle, reading the current wireless signal intensity value RⅠAnd RⅡJudging the obstacle type according to the obstacle distinguishing algorithm, if the obstacle is the obstacle, storing the wireless signal intensity value A [1 ]]=RⅠWalk along the obstacle on the left side, when | RⅠ-A[1]|>After that, the air conditioner is started to work,entering step 7; if the boundary is detected, entering the step 2;
(7) the mobile robot walks along the obstacle on the left side; when RⅠ-A[1]|<Returning to the step 6;
(8) and finishing the traversal path planning.
The center distance calculation algorithm is set as follows:
the translation distance s =10^ 10 [ (P-R)/(10 × n) ] -10^ 10 [ (P-A [0])/(10 × n) ], wherein P is ｃA wireless signal strength value RSSI measured at ｃA position one meter away from the first WIFI module, n is an environmental parameter, and is set to be 2 for ｃA home environment.
The left tracking process is set as follows: when R isⅠ>A[0]And the mobile robot rotates leftwards until A [0]]-<RⅠ<A[0]+; when R isⅠ<A[0]Rotate right until A [0]]-<RⅠ<A[0]+; keeping straight forward.
The right tracking process is set as follows: when R isⅠ>A[0]The mobile robot rotates to the right until A [0]]-<RⅠ<A[0]+; when R isⅠ<A[0]Rotate left until A [0]]-<RⅠ<A[0]+; keeping straight forward.
The obstacle differentiating algorithm is set as:
searching a in a Linked List LiAnd RⅠThe closest values, i.e. i = min, | ai - RⅠL reaches a minimum; i = min, if | bi- RⅡ|<And K, the current position is a boundary, otherwise, the current position is an obstacle, wherein K is a range limiting threshold.
The implementation of the invention has the positive effects that: 1. the wireless signal coverage is wide, and no accumulated error exists, so that the environment can be subjected to position marking, and traversal path planning is realized; 2. and the environment is not required to be set and modified, and the cost is low.
Drawings
FIG. 1 is a schematic diagram of a wireless signal distribution;
FIG. 2 is a schematic diagram of a traversal path planning process;
FIG. 3 is a functional block diagram of master electronics;
fig. 4 is a functional block diagram of the charge control electronics.
Detailed Description
The invention will now be further described with reference to the accompanying drawings in which:
referring to fig. 1-4, in the method for planning a traversal path of a mobile robot based on a dual wireless network, the mobile robot 19 includes a driving wheel, a driving motor 9 connected to the driving wheel, and a charging electrode male end 6 disposed at the front end of the mobile robot 19. Based on the driving wheels, the mobile robot 19 can move freely, and can be provided with two driving wheels and one supporting wheel; the male end 6 of the charging electrode is provided with two separated copper electrodes, and the charging is carried out when the charging electrode is connected with an external power supply.
A master control electronic device is arranged in the mobile robot 19, the master control electronic device includes a processor 1 for performing centralized control, the processor 1 may adopt a low-power microprocessor, specifically, MSP430 of TI corporation, or a common processor, such as a 32-bit ARM processor STM32F103C8T6 of ST corporation; the motor driving circuit 7 is connected with the processor 1, the motor driving circuit 7 is connected with the driving motor 9, under the control of the processor 1, the motor driving circuit 7 drives the driving motor 9, and the driving motor 9 drives the driving wheel to realize the free movement of the mobile robot 19; the obstacle detection circuit 8 is connected with the processor 1 and used for obstacle avoidance and path planning, and an ultrasonic sensor or an infrared sensor or a combination of the two sensors can be adopted; an inertial navigation system 10 connected to the processor 1, configured as an encoder mounted on the drive motor 9, for calculating the position (x, y) and direction θ of the mobile robot 19, the inertial navigation system 10 having an accumulated error due to calculation errors, mechanical play and ground slip, but having a small error over a period of time and having a use value; still include with the charging circuit 5 that processor 1 connects, charging circuit 5 with the public end 6 of charging electrode connect, 5 output connection rechargeable battery 4 of charging circuit, 4 output connection second power supply circuit 2 of rechargeable battery, second power supply circuit 2 provide the power for follow-up circuit.
The charging base 18 includes a charging electrode female terminal 17, a power jack, and charging control electronics. The power supply jack can be connected with an external power supply adapter to supply power to all components of the charging base 18; the female end 17 of the charging electrode is provided with two separated copper electrodes, has elasticity, corresponds to the male end 6 of the charging electrode, and has the same height of positive electrode to positive electrode and negative electrode to negative electrode.
The charging control electronic device is provided with a controller 12 for centralized control, and because the function is single, a PIC16F1503 singlechip of MICROCHIP can be adopted; the power supply comprises a first power supply circuit 13 and a filter circuit 14 connected with the power supply jack, and a switch tube 15 connected with the filter circuit 14, wherein the switch tube 15 is controlled by the controller 12, the output of the switch tube is connected with a current detection circuit 16, the current detection circuit 16 is connected with a charging electrode female terminal 17, the current detection circuit 16 converts a current signal into a voltage signal to the controller 12, and the controller 12 can control the magnitude of the output current and prevent the charging electrode female terminal 17 from being short-circuited.
The charging control electronic device is provided with a first WIFI module 11 connected with the controller 12, and the first WIFI module 11 is set to be in an AP mode, namely a wireless access point, and is a central node of a wireless network; the charging base 18 is characterized by further comprising an auxiliary network device, wherein the auxiliary network device is provided with a second WIFI module, the second WIFI module is set to be in an AP mode, and the auxiliary network device and the charging base 18 are arranged at different positions.
The main control electronic device is provided with a third WIFI module 3 connected with the processor 1, the third WIFI module 3 is set to be in an STA mode, namely a wireless station which is a terminal of a wireless network, the processor 1 acquires a wireless signal strength value RSSI received by the third WIFI module 3, the RSSI is recorded as R, and the RSSI is specifically a wireless signal strength value R of the first WIFI moduleⅠAnd saidWireless signal intensity value R of second WIFI moduleⅡ. The first WIFI module 11, the second WIFI module and the third WIFI module 3 can be set as IOT chips ESP8266, which has the advantages of low price and convenience.
The setting linked list L = { (a)i,bi) In which a isi=RⅠ i，bi=RⅡ iI =0,1,2,3Ⅰ iAnd RⅡ iThe wireless signal intensity values of the first WIFI module and the second WIFI module at equidistant positions of the working environment boundary are linear linked list data structures, namely environment maps, established by the mobile robot 19 in the process of walking along the boundary, and the spacing distance can be set to be 10 cm. The processor 1 sends AT + CWLAP to the third WIFI module 3 by using the network names of the first WIFI module 11 and the second WIFI module as parameters, and can obtain the wireless network signal strength R of the current locationⅠAnd RⅡ。
The processor 1 sets and traverses a path planning method, the traversal path planning method includes the following steps:
(1) the processor 1 is internally provided with an array A = { A (0), A (1) }, wherein A (j) = RⅠ jJ =0,1, wherein RⅠ jA wireless signal strength value representing the first WIFI module 11 stored by the mobile robot 19; the mobile robot 19 leaves the charging base and stores the current wireless signal intensity value A [0]]=RⅠ；
The mobile robot 19 leaves the charging base 18 and stores an initial value a [0] of a wireless signal.
(2) The mobile robot 19 rotates leftwards and walks along the boundary, the translation distance s of the mobile robot 19 from the charging base 18 is calculated by adopting a center distance calculation algorithm, and when the translation distance s is reached>When W, then store the current wireless signal intensity value A [0]]=RⅠEntering step 3, wherein W is the width of the vehicle body of the mobile robot; if the wireless signal strength value RⅠ>A[0]Then enter intoStep 8;
the center distance calculation algorithm is set as follows:
the translation distance s =10^ 10 [ (P-R)/(10 × n) ] -10^ 10 [ (P-A [0])/(10 × n) ], wherein P is ｃA wireless signal strength value RSSI measured at ｃA position one meter away from the first WIFI module, n is an environmental parameter, and is set to be 2 for ｃA home environment.
The mobile robot 19 moves outward by a distance of one vehicle body width, and records the wireless signal strength value of the starting point to prepare for traversing path planning.
Meanwhile, if the mobile robot 19 does not move outward by a distance of one body width, it moves toward the charging base 18, i.e., RⅠ>A[0]Then the mobile robot 19 is at the farthest position and the traversal path planning has been completed.
(3) The mobile robot 19 enters a leftward tracking process, and the tracking path is the wireless signal intensity RⅠThe contour of (A), i.e. the radio signal strength is A0]A path of (a); when the mobile robot 19 detects an obstacle, the current wireless signal strength value R is readⅠAnd RⅡJudging the obstacle type according to the obstacle distinguishing algorithm, if the obstacle is the obstacle, storing the wireless signal intensity value A [1 ]]=RⅠWalk along the obstacle on the left side, when | RⅠ-A[1]|>Then, entering step 4; if the boundary is detected, entering step 5;
the left tracking process is set as follows: when R isⅠ>A[0]+ the mobile robot 19 rotates to the left until A [0]]-<RⅠ<A[0]+; when R isⅠ<A[0]Rotate right until A [0]]-<RⅠ<A[0]+; keeping straight forward.
Because the wireless signals are radiated outwards by taking the emission source as the center, the signal intensity is reduced along with the increase of the distance, the continuity is realized, the traversing path planning can be realized by walking along the wireless signal intensity contour lines and keeping the distance of a vehicle body distance between the two wireless signal intensity contour lines.
When the mobile robot 19 detects an obstacle, it cannot determine whether the obstacle is an obstacle or a boundary, and therefore, it is necessary to perform a discrimination determination and then perform a separate process.
The obstacle differentiating algorithm is set as:
searching a in a Linked List LiAnd RⅠThe closest values, i.e. i = min, | ai - RⅠL reaches a minimum;
i = min, if | bi - RⅡ|<And K, the current position is a boundary, otherwise, the current position is an obstacle, wherein K is a range limiting threshold.
Because two WIFI modules are arranged and are arranged at different positions, two crossed wireless networks are formed, and the wireless signal intensity R isⅠOn the contour of (2), R at each placeⅡThe values are different, and it can be determined whether the current obstacle is a boundary or an obstacle from the data in the environment map L.
(4) The mobile robot 19 walks along the obstacle with the left side when | R |)Ⅰ-A[1]|<Returning to the step 3;
the mobile robot 19 performs obstacle detouring.
(5) The mobile robot 19 rotates rightwards and walks along the wall at the right side, the translation distance s between the mobile robot 19 and the charging base 18 is calculated by adopting a center distance calculation algorithm, and when the translation distance s is reached>When W, then store the current wireless signal intensity value A [0]]=RⅠEntering step 6; if the wireless signal strength value RⅠ>A[0]Entering step 8;
and 5, moving the other side of the vehicle body by the width of the vehicle body in the same step 2, and judging the condition of finishing the traversal path planning.
(6) The mobile robot 19 enters a rightward tracking process, and the tracking path is the wireless signal intensity RⅠThe contour of (A), i.e. the radio signal strength is A0]A path of (a); when the mobile robot 19 encounters an obstacle, the current wireless signal strength value R is readⅠAnd RⅡJudging the obstacle type according to the obstacle distinguishing algorithm, if the obstacle is the obstacle, storing the wireless signal intensity value A [1 ]]=RⅠTo do so byLeft side walking along the obstacle when RⅠ-A[1]|>Then, the step 7 is carried out; if the boundary is detected, entering the step 2;
the right tracking process is set as follows: when R isⅠ>A[0]+ the mobile robot 19 rotates right until A [0]]-<RⅠ<A[0]+; when R isⅠ<A[0]Rotate left until A [0]]-<RⅠ<A[0]+; keeping straight forward.
Step 6 is the same as step 3, and the process of planning the traversal path to the right is performed.
(7) The mobile robot walks along the obstacle on the left side; when RⅠ-A[1]|<Returning to the step 6;
the mobile robot 19 performs obstacle detouring.
(8) And finishing the traversal path planning.
In summary, the present invention establishes a dual wireless network, performs location labeling for the environment, and can perform traversal path planning based on the previously established environment map, distinguish the obstacle from the boundary, and implement high-efficiency path planning.
Claims (5)
1. A mobile robot traversal path planning method based on double wireless networks is provided, the mobile robot comprises a driving wheel, a driving motor connected with the driving wheel and a charging electrode male end arranged at the front end of the mobile robot, a master control electronic device is arranged in the mobile robot, the master control electronic device comprises a processor for performing centralized control, a motor driving circuit connected with the processor, the motor driving circuit is connected with the driving motor, an obstacle detection circuit connected with the processor is used for performing obstacle avoidance and path planning, an inertial navigation system connected with the processor is used for calculating the position (x, y) and the direction theta of the mobile robot, and the mobile robot traversal path planning method further comprises a charging circuit connected with the processor, and the charging circuit is connected with the charging electrode male end, the output of the charging circuit is connected with a rechargeable battery, the output of the rechargeable battery is connected with a second power supply circuit, and the second power supply circuit isThe subsequent circuit provides power supply; the base that charges includes female end of charging electrode, power jack to and the control electron device that charges, the control electron device that charges set up the controller that carries out centralized control, with first power supply circuit and the filter circuit that power jack connects, with the switch tube that filter circuit connects, the switch tube by controller control, output connection current detection circuit, current detection circuit connect the female end of charging electrode, current detection circuit convert current signal into voltage signal and give the controller, its characterized in that: the charging control electronic device is provided with a first WIFI module connected with the controller, and the first WIFI module is set to be in an AP mode; the charging base is provided with a first WIFI module, the first WIFI module is set to be in an AP mode, and the charging base is arranged at a position different from the position of the charging base; the main control electronic device is provided with a third WIFI module connected with the processor, the third WIFI module is set to be in an STA mode, the processor acquires a wireless signal strength value RSSI received by the third WIFI module, the RSSI is recorded as R, and the wireless signal strength value R is specifically received by the first WIFI moduleⅠAnd the wireless signal intensity value R of the second WIFI moduleⅡ(ii) a The processor setting linked list L = { (a)i,bi) In which a isi=RⅠ i，bi=RⅡ iI =0,1,2,3Ⅰ iAnd RⅡ iThe wireless signal strength values of the first WIFI module and the second WIFI module at the equidistant positions of the working environment boundary are obtained; and a traversal path planning method arranged in the processor, the traversal path planning method comprising the following steps:
(1) the processor is internally provided with an array A = { A [0]],A[1]In which A [ j ]]=RⅠ jJ =0,1, wherein RⅠ jRepresenting a wireless signal strength value of the first WIFI module stored by the mobile robot; said mobile robot leaving saidA charging base for storing the current wireless signal strength value A [0]]=RⅠ；
(2) The mobile robot rotates leftwards and walks along the boundary, the translation distance s from the mobile robot to the charging base is calculated by adopting a center distance calculation algorithm, and when the translation distance s is reached>When W, then store the current wireless signal intensity value A [0]]=RⅠEntering step 3, wherein W is the width of the vehicle body of the mobile robot; if the wireless signal strength value RⅠ>A[0]Entering step 8;
(3) the mobile robot enters a leftward tracking process, and the tracking path is wireless signal intensity RⅠThe contour of (A), i.e. the radio signal strength is A0]A path of (a); when the mobile robot detects an obstacle, reading the current wireless signal intensity value RⅠAnd RⅡJudging the obstacle type according to the obstacle distinguishing algorithm, if the obstacle is the obstacle, storing the wireless signal intensity value A [1 ]]=RⅠWalk along the obstacle on the left side, when | RⅠ-A[1]|>Then, entering step 4; if the boundary is detected, entering step 5;
(4) the mobile robot walks along the obstacle on the left side when the absolute value of R isⅠ-A[1]|<Returning to the step 3;
(5) the mobile robot rotates rightwards and walks along the wall at the right side, the center distance calculation algorithm is adopted to calculate the distance between the mobile robot and the charging base, and when the distance is s, the mobile robot moves away>When W, then store the current wireless signal intensity value A [0]]=RⅠEntering step 6; if the wireless signal strength value RⅠ>A[0]Entering step 8;
(6) the mobile robot enters a rightward tracking process, and the tracking path is the wireless signal intensity RⅠThe contour of (A), i.e. the radio signal strength is A0]A path of (a); when the mobile robot meets an obstacle, reading the current wireless signal intensity value RⅠAnd RⅡJudging the obstacle type according to the obstacle distinguishing algorithm, if the obstacle is the obstacle, storing the wireless signal intensity value A [1 ]]=RⅠWalk along the obstacle on the left side while guidingRⅠ-A[1]|>Then, the step 7 is carried out; if the boundary is detected, entering the step 2;
(7) the mobile robot walks along the obstacle on the left side; when RⅠ-A[1]|<Returning to the step 6;
(8) and finishing the traversal path planning.
2. The method for planning the traversal path of the mobile robot based on the dual wireless networks as claimed in claim 1, wherein: the center distance calculation algorithm is set as follows:
the translation distance s =10^ 10 [ (P-R)/(10 × n) ] -10^ 10 [ (P-A [0])/(10 × n) ], wherein P is ｃA wireless signal strength value RSSI measured at ｃA position one meter away from the first WIFI module, n is an environmental parameter, and is set to be 2 for ｃA home environment.
3. The method for planning the traversal path of the mobile robot based on the dual wireless networks as claimed in claim 1, wherein: the left tracking process is set as follows: when R isⅠ>A[0]And the mobile robot rotates leftwards until A [0]]-<RⅠ<A[0]+; when R isⅠ<A[0]Rotate right until A [0]]-<RⅠ<A[0]+; keeping straight forward.
4. The method for planning the traversal path of the mobile robot based on the dual wireless networks as claimed in claim 1, wherein: the right tracking process is set as follows: when R isⅠ>A[0]The mobile robot rotates to the right until A [0]]-<RⅠ<A[0]+; when R isⅠ<A[0]Rotate left until A [0]]-<RⅠ<A[0]+; keeping straight forward.
5. The method for planning the traversal path of the mobile robot based on the dual wireless networks as claimed in claim 1, wherein: the obstacle differentiating algorithm is set as:
searching a in a Linked List LiAnd RⅠThe closest values, i.e. i = min, | ai - RⅠ| daTo a minimum; i = min, if | bi - RⅡ|<And K, the current position is a boundary, otherwise, the current position is an obstacle, wherein K is a range limiting threshold.
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| CN109991980B (en) * | 2019-04-01 | 2022-07-08 | 珠海一微半导体股份有限公司 | Method for forming signal quantization distribution diagram of charging seat |
| US20240069549A1 (en) * | 2022-08-31 | 2024-02-29 | Positec Power Tools (Suzhou) Co., Ltd. | Island/border distinguishing for a robot lawnmower |
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