CN111942374A - Obstacle map generation method and device, vehicle and storage medium - Google Patents
Obstacle map generation method and device, vehicle and storage medium Download PDFInfo
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- CN111942374A CN111942374A CN202010820959.5A CN202010820959A CN111942374A CN 111942374 A CN111942374 A CN 111942374A CN 202010820959 A CN202010820959 A CN 202010820959A CN 111942374 A CN111942374 A CN 111942374A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units, or advanced driver assistance systems for ensuring comfort, stability and safety or drive control systems for propelling or retarding the vehicle
- B60W30/06—Automatic manoeuvring for parking
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2552/00—Input parameters relating to infrastructure
- B60W2552/50—Barriers
Abstract
The invention discloses a method and a device for generating an obstacle map, a vehicle and a storage medium. The method comprises the following steps: establishing an obstacle map area according to a first vehicle position at a first moment; determining alternative positions of all obstacles and corresponding alternative probabilities of the obstacles in the obstacle map area according to the acquired radar signals of the vehicle; and determining the candidate positions of the obstacles with the candidate probability of the obstacles being greater than or equal to the preset probability as target positions of the obstacles, and marking the target positions of the obstacles in the area of the obstacle map to form the obstacle map. The invention solves the problem that the radar detection device can only measure the distance of the obstacles around the vehicle and can not accurately judge the position of the obstacles to meet the parking requirement, realizes that the obstacle map around the vehicle can be established only by radar detection in the moving process of the vehicle, more accurately reflects the distribution effect of the obstacles around the vehicle and improves the safety in the moving process of the vehicle.
Description
Technical Field
The embodiment of the invention relates to the technical field of information processing, in particular to a method and a device for generating an obstacle map, a vehicle and a storage medium.
Background
With the development of science and technology and the development of times, people have higher and higher requirements on the convenience and safety of automobiles.
For the automatic parking function of the vehicle, it is very important for path planning whether barrier information around the vehicle can be accurately judged, and the inaccurate sensing of the barrier information can cause vehicle scratch in the parking process. When the vehicle collects the surrounding obstacle information, a visual sensor such as a camera or an electromagnetic wave sensor such as a radar can be used. The visual sensors such as the camera can establish a relatively accurate obstacle map under most working conditions, but the relative cost of the visual sensors is relatively high, so that the hardware cost of the vehicle is increased undoubtedly, and in addition, the visual sensors such as the camera have relatively strict requirements on the working environment, so that the obstacle map established based on the visual sensors has relatively large error under the condition of insufficient light conditions, and the obstacle information around the vehicle cannot be accurately reflected. The existing electromagnetic wave sensors such as radar can only measure the distance of obstacles around the vehicle, can not accurately judge the position of the obstacles, and can not meet the requirements of a parking system.
Disclosure of Invention
The invention provides a method and a device for generating an obstacle map, a vehicle and a storage medium, which can realize the effect that the obstacle map around the vehicle can be accurately established only by radar detection in the moving process of the vehicle.
In a first aspect, an embodiment of the present invention provides an obstacle map generation method, including:
establishing an obstacle map area according to a first vehicle position at a first moment;
determining alternative positions of all obstacles and corresponding alternative probabilities of the obstacles in the obstacle map area according to the acquired radar signals of the vehicle;
and determining the candidate positions of the obstacles with the candidate probability of the obstacles being greater than or equal to the preset probability as target positions of the obstacles, and marking the target positions of the obstacles in the area of the obstacle map to form the obstacle map.
Optionally, the establishing an obstacle map area according to the vehicle position at the first time includes:
the method comprises the steps of obtaining a first vehicle position at a first moment, and determining a vehicle position area with a preset area by taking the first vehicle position as an origin;
dividing the vehicle position area into a preset number of area blocks, and determining the preset number of area blocks as an obstacle map area.
Optionally, the determining, according to the acquired vehicle radar signal, each obstacle candidate position and a corresponding obstacle candidate probability in the obstacle map area includes:
periodically acquiring vehicle radar signals, and determining cycle alternative positions and corresponding cycle alternative probabilities of obstacle information in the vehicle radar signals aiming at the vehicle radar signals acquired each time;
and weighting and summing the cycle alternative probabilities with the same cycle alternative positions in the preset cycle number according to a preset weighting coefficient to obtain the alternative positions of the obstacles and the corresponding alternative probabilities of the obstacles.
Optionally, the determining the cycle candidate positions and the corresponding cycle candidate probabilities of the obstacle information in the vehicle radar signal includes:
determining the barrier distance between the barrier in each barrier information and the current vehicle position and the acquisition angle of the vehicle radar signal according to the vehicle radar signal;
for each piece of obstacle information, determining the region block where the point which is within the acquisition angle and away from the current vehicle position by the obstacle distance is located as a periodic alternative position;
and determining the cycle alternative probability corresponding to the cycle alternative positions according to the number of the cycle alternative positions.
Optionally, the method further includes:
and monitoring the candidate obstacle probability corresponding to each candidate obstacle position, and if the candidate obstacle probability does not change within a preset failure period number, setting the candidate obstacle probability to zero.
Optionally, after the obstacle map area is established according to the first vehicle position at the first time, the method further includes:
acquiring a second vehicle position at a second moment, and determining the minimum distance between the second vehicle position and the edge of the obstacle map area;
and if the minimum distance is smaller than a preset critical distance, updating the obstacle map area according to the second vehicle position.
Optionally, before determining each candidate obstacle position and the corresponding candidate obstacle probability in the obstacle map area, the method further includes:
and filtering the vehicle radar signal.
In a second aspect, an embodiment of the present invention further provides an obstacle map generating apparatus, where the apparatus includes:
the map area establishing module is used for establishing an obstacle map area according to a first vehicle position at a first moment;
the alternative area probability determining module is used for determining alternative positions of all obstacles and corresponding alternative probabilities of the obstacles in the obstacle map area according to the acquired radar signals of the vehicle;
and the obstacle map forming module is used for determining the obstacle candidate position with the obstacle candidate probability greater than or equal to the preset probability as an obstacle target position, and marking the obstacle target position in the obstacle map area to form an obstacle map.
In a third aspect, an embodiment of the present invention further provides a vehicle, including:
one or more processors;
a memory for storing one or more programs;
a radar for collecting obstacle information around the vehicle;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement an obstacle mapping method according to any embodiment of the present invention.
In a fourth aspect, embodiments of the present invention further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform the method of generating an obstacle map according to any of the embodiments of the present invention.
According to the method, the alternative positions of the obstacles and the corresponding alternative probabilities of the obstacles are determined in the obstacle map area through the acquired radar signals of the vehicle, the alternative positions of the obstacles with the alternative probabilities of more than or equal to the preset probability are determined as the target positions of the obstacles, and the target positions of the obstacles are marked in the obstacle map area to form the obstacle map, so that the problem that a radar detection device can only measure the distances of the obstacles around the vehicle and cannot accurately judge the positions of the obstacles to meet the parking requirement is solved, the obstacle map around the vehicle can be established only by radar detection in the moving process of the vehicle, the effect of accurately reflecting the distribution of the obstacles around the vehicle is achieved, and the safety in the moving process of the vehicle is improved.
Drawings
Fig. 1 is a flowchart of an obstacle map generation method according to an embodiment of the present invention;
fig. 2 is a flowchart of an obstacle map generating method according to a second embodiment of the present invention;
fig. 3 is a flowchart for determining periodic alternative positions and corresponding periodic alternative probabilities of each obstacle information in a vehicle radar signal in the obstacle map generation method according to the second embodiment of the present invention;
fig. 4 is a schematic diagram illustrating an obstacle map area established in an obstacle map generation method according to a second embodiment of the present invention;
fig. 5 is a schematic diagram of filtering a vehicle radar signal in an obstacle map generation method according to a second embodiment of the present invention;
fig. 6 is a schematic diagram of determining periodic alternative positions in an obstacle map generation method according to a second embodiment of the present invention;
fig. 7 is a schematic diagram illustrating an updated obstacle map area in an obstacle map generation method according to a second embodiment of the present invention;
fig. 8 is a block diagram of a structure of an obstacle map generating apparatus according to a third embodiment of the present invention;
fig. 9 is a block diagram of a vehicle according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only a part of the structures related to the present invention, not all of the structures, are shown in the drawings, and furthermore, embodiments of the present invention and features of the embodiments may be combined with each other without conflict.
Example one
Fig. 1 is a flowchart of an obstacle map generation method according to an embodiment of the present invention, where the embodiment is applicable to a situation where an obstacle map around a vehicle is created through radar signals during movement of the vehicle, and the method may be executed by an obstacle map generation device, and the device may be implemented by software and/or hardware.
As shown in fig. 1, the method specifically includes the following steps:
The first time can be understood as the time when the vehicle enters a parking operation or other times when the obstacle map needs to be generated, and the first time is the initial time when the obstacle map is generated. Accordingly, the first vehicle position may be understood as the geographical position of the vehicle at the first time, and the position of the vehicle may be represented by the horizontal position of the midpoint of the rear axle of the vehicle, or may be represented by the horizontal position of mass points of the vehicle. The obstacle map area may be understood as an area where it is necessary to determine the presence or absence of an obstacle and the specific position of the obstacle.
Specifically, when the user has a parking demand or needs to check the situation of obstacles around the vehicle, the user may send an obstacle map generation instruction actively or by the vehicle control system, and when the vehicle obstacle map generation device receives the obstacle map generation instruction, the vehicle obstacle map generation device determines that the time is the first time, and obtains the position of the vehicle at the first time as the first vehicle position. An area of a certain range around the first vehicle position may be selected as the obstacle map area. When an area in a certain range around the first vehicle position is selected, adjustment can be performed according to user requirements, for example, if a user wants to back up at the moment, a larger area behind the vehicle and a smaller area in front of the vehicle can be selected as an obstacle map area; if the user wants to park to the right side of the vehicle at the moment, a larger area on the right side of the vehicle and a smaller area on the left side of the vehicle can be selected as an obstacle map area; if the user only wants to observe the situation of the obstacles around the vehicle, a quadrilateral area can be selected by taking the first vehicle position as the center, or a circular area can be selected by taking the first vehicle position as the center of a circle to serve as the obstacle map area.
And step 120, determining candidate positions of all obstacles and corresponding candidate probabilities of the obstacles in the obstacle map area according to the acquired radar signals of the vehicle.
Wherein, the alternative position of the obstacle can be understood as the position where the obstacle may exist. The obstacle candidate probability may be understood as the possibility that an obstacle exists at an obstacle candidate position.
Specifically, because the radar can only detect the distance from the obstacle to the vehicle, and the radar detection range is a sector area, when the radar detects that the obstacle appears at a certain distance from the vehicle, the obstacle may exist at the point of the distance from the vehicle in the sector area. Positions where obstacles may exist can be labeled according to distance information of the obstacles in the radar signals of the vehicle, the positions are used as alternative positions of the obstacles, and the probability that the obstacles exist in the positions is analyzed. The method can continuously acquire the radar signals of the vehicle in the moving process of the vehicle, increase and adjust the alternative positions of the obstacles according to the acquired radar signals of the vehicle each time, and re-determine the alternative probability of the obstacles corresponding to the alternative positions of the obstacles. For example, after the vehicle radar signal is acquired for the first time, there may be an obstacle at each of position 1, position 2, position 3, and position 4, and the probability of the obstacle being present is a, respectively, and after the vehicle radar signal is acquired for the second time, there may be an obstacle at each of position 3, position 5, position 6, and position 7, and the probability of the obstacle being present is B, respectively, and in combination with these two sets of vehicle radar signals, it is considered that the probability of the obstacle being present at position 3 is greater, and the obstacle candidate probability corresponding to position 3 may be determined as C, C > a, and C > B.
And step 130, determining the candidate positions of the obstacles with the candidate probability of the obstacles being greater than or equal to the preset probability as target positions of the obstacles, and marking the target positions of the obstacles in the map area of the obstacles to form a map of the obstacles.
The preset probability can be understood as a judgment value for determining whether the obstacle exists, when the candidate probability of the obstacle is greater than or equal to the preset probability, the corresponding candidate position of the obstacle can be considered to have the obstacle, and correspondingly, when the candidate probability of the obstacle is less than the preset probability, the corresponding candidate position of the obstacle can be considered to have no obstacle. The obstacle target position may be understood as a position where an obstacle is present.
Specifically, the vehicle radar signal can be continuously acquired in the moving process of the vehicle, each obstacle candidate position and the corresponding obstacle candidate probability are continuously updated through the step 120, when the obstacle candidate probability is greater than or equal to the preset probability, the obstacle candidate position corresponding to the obstacle candidate probability is determined as the obstacle target position, the determined obstacle target position is marked in the obstacle map area, and the obstacle map is continuously improved.
According to the technical scheme, the alternative positions of the obstacles and the corresponding alternative probabilities of the obstacles are determined in the obstacle map area through the acquired radar signals of the vehicle, the alternative positions of the obstacles with the alternative probabilities of more than or equal to the preset probability are determined as the target positions of the obstacles, and the target positions of the obstacles are marked in the obstacle map area to form the obstacle map, so that the problem that a radar detection device can only measure the distance of the obstacles around the vehicle and cannot accurately judge the positions of the obstacles to meet the parking requirement is solved, the obstacle map around the vehicle can be established only by radar detection in the moving process of the vehicle, the distribution effect of the obstacles around the vehicle is accurately reflected, and the safety of the vehicle in the moving process is improved.
Example two
Fig. 2 is a flowchart of a method for generating an obstacle map according to a second embodiment of the present invention. The present embodiment further optimizes the obstacle map generation method based on the above-described embodiment.
As shown in fig. 2, the method specifically includes:
The preset area can be determined according to the radar detection range, and can also be set according to different scenes. The vehicle position area may be understood as an area range where it is necessary to acquire information on obstacles around the vehicle.
Specifically, when the user has a parking demand or needs to check the situation of obstacles around the vehicle, the user may send an obstacle map generation instruction actively or by the vehicle control system, and when the vehicle obstacle map generation device receives the obstacle map generation instruction, the vehicle obstacle map generation device determines that the time is the first time, and obtains the position of the vehicle at the first time as the first vehicle position. A region of a predetermined area around the first vehicle location may be selected as the vehicle location region. For example, a quadrangular area may be selected as the vehicle position area centering on the first vehicle position.
And step 220, dividing the vehicle position area into a preset number of area blocks, and determining the preset number of area blocks as the obstacle map area.
The area block can be understood as a smaller area block which divides the vehicle position area, so that the specific position of the obstacle can be marked conveniently.
Specifically, the vehicle position area may be divided into a preset number of area blocks according to a certain division rule, for example, the vehicle position area of one quadrangle may be divided into a plurality of small quadrangle area blocks with equal areas. An area composed of all the area blocks may be determined as an obstacle map area.
And step 230, filtering the vehicle radar signals, and periodically acquiring the vehicle radar signals.
Specifically, the radar data collected by the vehicle often has a continuous one-frame or two-frame jump condition, so that the radar data with the continuous one-frame or two-frame data jumping frequently can be removed. The obstacle map generating device may continuously obtain the vehicle radar signal at a certain periodic interval after filtering the vehicle radar signal, for example, obtain the vehicle radar signal once every 50 ms.
And 240, determining the cycle alternative positions and the corresponding cycle alternative probabilities of the obstacle information in the vehicle radar signals aiming at the vehicle radar signals acquired each time.
The obstacle information can be understood as information related to the detection of the obstacle by the vehicle radar, and a plurality of pieces of obstacle information can be included in the vehicle radar signal acquired each time. The periodic candidate position may be understood as a position where an obstacle may exist, which is obtained through the vehicle radar signal acquired in one period, and the periodic candidate probability may be understood as a possibility that an obstacle exists at a certain periodic candidate position, which is determined through the vehicle radar signal acquired this time.
Optionally, as shown in fig. 3, determining the cycle candidate positions and the corresponding cycle candidate probabilities of each obstacle information in the vehicle radar signal in step 240 may be performed through the following specific steps:
The current vehicle position can be understood as the position of the vehicle when the radar signal of the vehicle is obtained at this time, the current vehicle position can be represented by one point in the process of determining the obstacle map and is consistent with the selection mode of the first vehicle position, and when the first vehicle position is represented by the horizontal position of the middle point of the rear axle of the vehicle, the current vehicle position is also represented by the horizontal position of the middle point of the rear axle of the vehicle; when the first vehicle position is represented by a horizontal position of a vehicle mass point, the current vehicle position is also represented by the horizontal position of the vehicle mass point. The obstacle distance may be understood as the length of space of the obstacle detected by the radar from the current vehicle position. The collection angle can be used to represent the angular range of the radar-transmitted signal of the vehicle.
Specifically, because the radar detection range is a sector area and only the distance between the obstacle and the vehicle can be detected, the acquisition angle of the radar signal of the vehicle and the obstacle distance between the obstacle and the current vehicle position can be obtained to determine the position range of the obstacle.
Specifically, when the radar detects that an obstacle exists at a position away from the current vehicle position by an obstacle distance, in an angle range of a signal transmitted by the radar, the position away from the current vehicle position by the obstacle distance is likely to be a position where the obstacle exists.
Specifically, since it is possible that, within the angular range of the radar transmission signal, the positions distant from the current vehicle position by the obstacle distance are positions where the obstacle exists, and the probabilities of the obstacles theoretically being equal, the cycle candidate probabilities corresponding to the cycle candidate positions may be determined to be the same probability, and the probability value may be the inverse of the number of the cycle candidate positions.
Optionally, if a plurality of radar devices are installed on the vehicle, in a vehicle radar signal acquired at one time, obstacle information acquired by two radars determines a cycle candidate position at the same time, then the probability of the cycle candidate position determined by one of the obstacle information may be selected as a corresponding cycle candidate probability, and the probabilities of the cycle candidate positions determined by the two obstacle information respectively may also be calculated by performing weighted summation to obtain probabilities as corresponding cycle candidate probabilities.
And step 250, carrying out weighted summation on the cycle alternative probabilities with the same cycle alternative positions in the preset cycle number according to a preset weighting coefficient to obtain the alternative positions of the obstacles and the corresponding alternative probabilities of the obstacles.
Specifically, each obstacle candidate position and the corresponding obstacle candidate probability can be calculated through each cycle candidate position determined by the continuous preset cycle number and the corresponding cycle candidate probability. The cycle alternative probabilities corresponding to the cycle alternative positions at the same position in each cycle alternative position can be weighted and summed according to a preset weighting coefficient, all the cycle alternative positions determined in the preset cycle number are used as obstacle alternative positions, and the probability calculated by the weighted and summed cycle alternative probabilities is used as the obstacle alternative probability corresponding to each obstacle alternative position. For example, a cycle candidate position determined by three vehicle radar signals closest to the current time and corresponding cycle candidate probabilities are obtained, where in the obtained first vehicle radar signal, all of position 1, position 2, position 3 and position 4 may have obstacles, then all of position 1, position 2, position 3 and position 4 are cycle candidate positions of the first vehicle radar signal, and corresponding cycle candidate probabilities are a, respectively, in the obtained second vehicle radar signal, all of position 3, position 4, position 5, position 6 and position 7 may have obstacles, then all of position 3, position 4, position 5, position 6 and position 7 are cycle candidate positions of the second vehicle radar signal, and the probabilities of existence of obstacles are B, respectively, in the obtained third vehicle radar signal, all of position 4, position 5, position 8 and position 9 may have obstacles, then position 4, position 5, position 8 and position 9 are all periodic candidate positions for the third time vehicle radar signal, with a probability of obstacle presence of C, respectively. When the preset weighting coefficients are all 1, combining the three vehicle radar signals, it can be obtained that the obstacle candidate positions include position 1, position 2, position 3, position 4, position 5, position 6, position 7, position 8 and position 9, the obstacle candidate probability corresponding to the position 1 is a, the obstacle candidate probability corresponding to the position 2 is a, the obstacle candidate probability corresponding to the position 3 is a + B, the obstacle candidate probability corresponding to the position 4 is a + B + C, the obstacle candidate probability corresponding to the position 5 is B + C, the obstacle candidate probability corresponding to the position 6 is B, the obstacle candidate probability corresponding to the position 7 is B, the obstacle candidate probability corresponding to the position 8 is C, and the obstacle candidate probability corresponding to the position 9 is C.
And step 260, determining the candidate positions of the obstacles with the candidate probability of the obstacles being greater than or equal to the preset probability as target positions of the obstacles, and marking the target positions of the obstacles in the map area of the obstacles to form a map of the obstacles.
Specifically, each obstacle candidate position and the corresponding obstacle candidate probability may be continuously updated through step 250, and when the obstacle candidate probability is greater than or equal to the preset probability, the obstacle candidate position corresponding to the obstacle candidate probability is determined as an obstacle target position, and the determined obstacle target position is labeled in the obstacle map area, so as to continuously refine the obstacle map.
And 270, monitoring the candidate probability of the obstacle corresponding to each candidate position of the obstacle, and if the candidate probability of the obstacle does not change within the preset failure cycles, setting the candidate probability of the obstacle to zero.
If a certain obstacle candidate position is obtained through a certain vehicle radar signal, and no obstacle possibly existing in the obstacle candidate position is detected in the following vehicle radar signals, the obstacle candidate position can be considered to be free of obstacles, and the interval period number for determining that no obstacle exists in the obstacle candidate position can be defined as a preset failure period number.
Specifically, after a certain position is determined to be an obstacle candidate position, the obstacle candidate probability corresponding to the certain position may be monitored, and if the obstacle candidate probability remains unchanged within a preset number of failure cycles, it may be considered that no obstacle exists in the obstacle candidate position, and the obstacle candidate probability corresponding to the obstacle candidate position is set to zero.
And step 280, acquiring a second vehicle position at a second moment, and determining the minimum distance between the second vehicle position and the edge of the obstacle map area.
The second time may be any time after the first time, the second time does not represent a fixed time after the first time, and the second time may be updated continuously, for example, the second time is updated every 1 s. The second vehicle position is the position of the vehicle at the second moment, the selection mode of the second vehicle position is consistent with that of the first vehicle position, and when the first vehicle position is represented by the horizontal position of the midpoint of the rear axle of the vehicle, the second vehicle position is also represented by the horizontal position of the midpoint of the rear axle of the vehicle at the second moment; when the first vehicle position is represented by the horizontal position of the mass of the vehicle, the second vehicle position is also represented by the horizontal position of the mass of the vehicle at the second time. The obstacle map area edge may be understood as an edge line of the obstacle map area.
Specifically, after the first time is determined, the obstacle map generating device may monitor the position of the vehicle in real time, determine the time after a certain time interval between the first time and the second time as the second time, acquire the position of the vehicle at the second time as the second vehicle position, and detect the distance from the second vehicle position to each point on the edge of the obstacle map area to obtain the minimum distance between the second vehicle position and the edge of the obstacle map area.
And 290, if the minimum distance is smaller than the preset critical distance, updating the obstacle map area according to the position of the second vehicle.
The vehicle may approach one side of the obstacle map area during movement, and when the vehicle is approaching the edge of one side of the obstacle map area, the vehicle may be considered to be likely to exit the obstacle map area. The preset threshold distance may be understood as a determination value that determines whether the vehicle is likely to move out of the obstacle map area, and when the vehicle is less than the edge preset threshold distance from the obstacle map area, it may be understood that the vehicle is likely to move out of the obstacle map area.
Specifically, the relationship between the minimum distance between the second vehicle position and the edge of the obstacle map area and the preset critical distance may be determined, and when the minimum distance is smaller than the preset critical distance, it may be determined that the vehicle may move out of the obstacle map area, and the obstacle map area may not be suitable for operations such as parking the vehicle, so that the obstacle map area needs to be determined again according to the second vehicle position. If there is an overlap area between the obstacle map area before and after the update, and there may be a determined obstacle target position in the overlap area, the annotation may be performed directly on the updated obstacle map area without re-measurement.
Optionally, when the minimum distance is not less than the preset threshold distance, it may be considered that the vehicle may not temporarily move out of the obstacle map area, so step 280 may be performed again, that is, the second vehicle position at the second time and the second time are obtained again, and the second vehicle position is determined.
For example, as shown in fig. 4, when a user needs to park a vehicle or needs to check the situation of obstacles around the vehicle, an obstacle map generation instruction is issued, a trigger time is taken as a first time, the position of the midpoint of the rear axle of the vehicle at the first time is a first vehicle position, the first vehicle position is taken as an origin, the direction of the longitudinal axis of the vehicle is taken as an x-axis, the left side direction perpendicular to the x-axis is taken as a y-axis, a vehicle coordinate system is established, the range of 50m × 50m around the first vehicle position is determined as a vehicle position area, the vehicle position area is divided into square area blocks with the side length k being 10cm, and 500 divided area blocks are determined as an obstacle map area. In this case, the obstacle map area may be represented by a bool type matrix of 500 × 500, the obstacle map area may grid the actual distance around the vehicle, one grid in the obstacle map area may represent an area of the actual size k × k, and the bool type matrix of 500 × 500 areas in the obstacle map area may be recorded with or without obstacles, and the obstacle may be represented by 0 and the obstacle may be represented by 1. As shown in fig. 4, minY represents the region segment, 1 in this example, of the minimum value of the ordinate in the region of the obstacle map, which ordinate is different from the y-axis of the vehicle coordinate system, and which ordinate represents the column number of the pool-type matrix. Accordingly, maxY represents the maximum ordinate of the obstacle map area, in this example 501, minX represents the minimum abscissa of the obstacle map, in this example 1, maxX represents the maximum abscissa of the obstacle map, in this example 501, the borol type matrix is initialized to 0. The ultrasonic radar arranged on the vehicle can be multiple, for example, 4 short-distance radars can be arranged in front of the vehicle, 4 short-distance radars can be arranged behind the vehicle, 2 long-distance radars can be arranged on the left side of the vehicle, and 2 long-distance radars can be arranged on the right side of the vehicle. In the working process of the parking system, the obstacle map generating device can periodically acquire the vehicle radar signals after filtering the vehicle radar signals, as shown in fig. 5, the data acquired by the vehicle ultrasonic radar can be filtered because the ultrasonic radar can not avoid interference. The radar data collected by the vehicle often has the condition that one or two continuous frames have jumping, so that the data with one or two continuous frames having frequent jumping can be eliminated. And determining the obstacle distance between the obstacle and the current vehicle position in each obstacle information and the acquisition angle of the vehicle radar signal aiming at the vehicle radar signal acquired each time. Because the distance data collected by the radar is the distance of the obstacle from the vehicle, a coordinate system change is required to convert the obstacle distance collected by the radar into an obstacle map area coordinate system. Since the radar measures the distance information of the obstacle from the vehicle, the possible coordinates of the obstacle in the vehicle coordinate system need to be obtained according to the distance of the obstacle. In this example, taking the conversion relationship of the distance from the obstacle detected by the radar on the left side of the vehicle to the obstacle map area as an example, the calculation can be performed by the following conversion relationship:
wherein RdL, RdW may respectively represent the distance of the radar relative to the x-axis and the y-axis of the vehicle coordinate system, pi may represent the radar collection angle, d may represent the obstacle distance collected by the radar, posvx、posvyThe abscissa and ordinate, respectively, of the position where the obstacle may exist, determined in the vehicle coordinates, of the obstacle distance acquired by the radar. The coordinates in the vehicle coordinate system may then be converted to coordinates in the global coordinate system, which may be calculated by the following conversion relationship:
wherein p isvx、pvyCan respectively represent the abscissa and the ordinate of the current vehicle position in the global coordinate system, pvyawCan represent the heading angle, pos, of the vehiclewx、poswyAn abscissa and an ordinate, respectively, which may represent the position where the obstacle may exist, determined in the global coordinate, from the obstacle distance acquired by the radar. Finally, the obstacle information under the global coordinate system is marked into the obstacle map area, and the calculation can be performed through the following conversion relation:
li、ljthe abscissa and ordinate of the obstacle in the obstacle map region can be represented, respectively. As shown in fig. 6, through the above calculation, the region block where the point where the obstacle may exist is determined as the period candidate position, and the period candidate position is determined according to the number of the period candidate positionsAnd selecting the periodic alternative probability corresponding to the position. And weighting and summing the cycle alternative probabilities with the same cycle alternative positions in the preset cycle number according to a preset weighting coefficient to obtain the alternative positions of the obstacles and the corresponding alternative probabilities of the obstacles. And determining the candidate positions of the obstacles with the candidate probability of the obstacles being greater than or equal to the preset probability as target positions of the obstacles, and marking the target positions of the obstacles in the area of the obstacle map to form the obstacle map. The obstacle map generating device may monitor the position of the vehicle in real time, and determine the minimum distance between the vehicle and the edge of the obstacle map area, as shown in fig. 7, when the vehicle moves to the edge of the obstacle map area and the distance is smaller than a preset threshold distance, the obstacle map area is updated.
The technical scheme of the embodiment includes that a vehicle position area is determined according to a first vehicle position at a first moment, the vehicle position area is divided into a preset number of areas and blocks to obtain an obstacle map area, specific positions of obstacles are marked conveniently, vehicle radar signals are filtered, vehicle radar signals are obtained periodically, period alternative positions and corresponding period alternative probabilities of obstacle information in the vehicle radar signals are determined according to the vehicle radar signals obtained each time, the period alternative probabilities with the same period alternative positions in a preset period number are weighted and summed according to a preset weighting coefficient to obtain the obstacle alternative positions and the corresponding obstacle alternative probabilities, the obstacle alternative positions with the obstacle alternative probabilities larger than or equal to the preset probability are determined as obstacle target positions, and an obstacle map is formed by annotating the obstacle target positions in the obstacle map area, meanwhile, the obstacle candidate probability corresponding to each obstacle candidate position is monitored, if the obstacle candidate probability is not changed within the preset failure cycles, the obstacle candidate probability is set to zero, the obstacle candidate position with low obstacle candidate probability is cleared, in addition, the second vehicle position at the second moment is monitored, when the minimum distance between the second vehicle position and the edge of the obstacle map area is smaller than the preset critical distance, the obstacle map area is updated according to the second vehicle position, the problem that the radar detection device can only measure the obstacle distance around the vehicle and cannot accurately judge the position of the obstacle to meet the parking requirement is solved, the obstacle map around the vehicle can be established only by radar detection in the moving process of the vehicle, the obstacle map is updated in real time according to the moving position of the vehicle, and the effect of accurately reflecting the obstacle distribution around the vehicle is achieved, the safety of the vehicle in the moving process is improved.
EXAMPLE III
The obstacle map generation device provided by the embodiment of the invention can execute the obstacle map generation method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method. Fig. 8 is a block diagram of a structure of an obstacle map generating apparatus according to a third embodiment of the present invention, and as shown in fig. 8, the apparatus includes: a map area establishing module 310, a candidate area probability determining module 320, and an obstacle mapping module 330.
The map area establishing module 310 is configured to establish an obstacle map area according to a first vehicle position at a first time.
And a candidate area probability determining module 320, configured to determine candidate positions of obstacles and corresponding candidate probabilities of the obstacles in the obstacle map area according to the acquired vehicle radar signal.
And an obstacle map forming module 330, configured to determine an obstacle candidate position where the obstacle candidate probability is greater than or equal to a preset probability as an obstacle target position, and mark the obstacle target position in the obstacle map area to form an obstacle map.
According to the technical scheme, the alternative positions of the obstacles and the corresponding alternative probabilities of the obstacles are determined in the obstacle map area through the acquired radar signals of the vehicle, the alternative positions of the obstacles with the alternative probabilities of more than or equal to the preset probability are determined as the target positions of the obstacles, and the target positions of the obstacles are marked in the obstacle map area to form the obstacle map, so that the problem that a radar detection device can only measure the distance of the obstacles around the vehicle and cannot accurately judge the positions of the obstacles to meet the parking requirement is solved, the obstacle map around the vehicle can be established only by radar detection in the moving process of the vehicle, the distribution effect of the obstacles around the vehicle is accurately reflected, and the safety of the vehicle in the moving process is improved.
Optionally, the map area establishing module 310 is specifically configured to:
the method comprises the steps of obtaining a first vehicle position at a first moment, and determining a vehicle position area with a preset area by taking the first vehicle position as an origin;
dividing the vehicle position area into a preset number of area blocks, and determining the preset number of area blocks as an obstacle map area.
Optionally, the candidate region probability determining module 320 includes:
and the periodic candidate position probability determining unit is used for periodically acquiring the vehicle radar signals and determining the periodic candidate positions and the corresponding periodic candidate probabilities of the obstacle information in the vehicle radar signals aiming at the vehicle radar signals acquired each time.
And the obstacle candidate position probability determining unit is used for weighting and summing the cycle candidate probabilities with the same cycle candidate positions in the preset cycle number according to a preset weighting coefficient to obtain the candidate positions of the obstacles and the corresponding obstacle candidate probabilities.
Optionally, the determining the cycle candidate positions and the corresponding cycle candidate probabilities of the obstacle information in the vehicle radar signal includes:
determining the barrier distance between the barrier in each barrier information and the current vehicle position and the acquisition angle of the vehicle radar signal according to the vehicle radar signal;
for each piece of obstacle information, determining the region block where the point which is within the acquisition angle and away from the current vehicle position by the obstacle distance is located as a periodic alternative position;
and determining the cycle alternative probability corresponding to the cycle alternative positions according to the number of the cycle alternative positions.
Optionally, the apparatus further includes an obstacle candidate position monitoring module 340, configured to:
and monitoring the candidate obstacle probability corresponding to each candidate obstacle position, and if the candidate obstacle probability does not change within a preset failure period number, setting the candidate obstacle probability to zero.
Optionally, the apparatus further comprises an obstacle map area monitoring module 350, configured to:
acquiring a second vehicle position at a second moment, and determining the minimum distance between the second vehicle position and the edge of the obstacle map area;
and if the minimum distance is smaller than a preset critical distance, updating the obstacle map area according to the second vehicle position.
Optionally, the apparatus further includes a signal processing module 360, configured to:
and filtering the vehicle radar signal.
The technical scheme of the embodiment includes that a vehicle position area is determined according to a first vehicle position at a first moment, the vehicle position area is divided into a preset number of areas and blocks to obtain an obstacle map area, specific positions of obstacles are marked conveniently, vehicle radar signals are filtered, vehicle radar signals are obtained periodically, period alternative positions and corresponding period alternative probabilities of obstacle information in the vehicle radar signals are determined according to the vehicle radar signals obtained each time, the period alternative probabilities with the same period alternative positions in a preset period number are weighted and summed according to a preset weighting coefficient to obtain the obstacle alternative positions and the corresponding obstacle alternative probabilities, the obstacle alternative positions with the obstacle alternative probabilities larger than or equal to the preset probability are determined as obstacle target positions, and an obstacle map is formed by annotating the obstacle target positions in the obstacle map area, meanwhile, the obstacle candidate probability corresponding to each obstacle candidate position is monitored, if the obstacle candidate probability is not changed within the preset failure cycles, the obstacle candidate probability is set to zero, the obstacle candidate position with low obstacle candidate probability is cleared, in addition, the second vehicle position at the second moment is monitored, when the minimum distance between the second vehicle position and the edge of the obstacle map area is smaller than the preset critical distance, the obstacle map area is updated according to the second vehicle position, the problem that the radar detection device can only measure the obstacle distance around the vehicle and cannot accurately judge the position of the obstacle to meet the parking requirement is solved, the obstacle map around the vehicle can be established only by radar detection in the moving process of the vehicle, the obstacle map is updated in real time according to the moving position of the vehicle, and the effect of accurately reflecting the obstacle distribution around the vehicle is achieved, the safety of the vehicle in the moving process is improved.
Example four
Fig. 9 is a block diagram of a vehicle according to a fourth embodiment of the present invention, as shown in fig. 9, the vehicle includes a processor 410, a memory 420, and at least one radar 430; the number of processors 410 in the vehicle may be one or more, and one processor 410 is taken as an example in fig. 9; the number of radars 430 in the vehicle may be one or more, and two radars 430 are exemplified in fig. 9; the processor 410, memory 420 and radar 430 in the vehicle may be connected by a bus or other means, as exemplified by the bus connection in fig. 9.
The memory 420 serves as a computer-readable storage medium, and may be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the obstacle map generation method in the embodiment of the present invention (for example, the map area establishing module 310, the candidate area probability determination module 320, and the obstacle map forming module 330 in the obstacle map generation apparatus). The processor 410 executes various functional applications and data processing of the vehicle, that is, implements the above-described obstacle map generation method, by executing software programs, instructions, and modules stored in the memory 420.
The memory 420 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 420 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the memory 420 may further include memory located remotely from the processor 410, which may be connected to the vehicle over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The radar 430 may be used to collect obstacle information around the vehicle.
EXAMPLE five
An embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor, perform a method for obstacle map generation, the method including:
establishing an obstacle map area according to a first vehicle position at a first moment;
determining alternative positions of all obstacles and corresponding alternative probabilities of the obstacles in the obstacle map area according to the acquired radar signals of the vehicle;
and determining the candidate positions of the obstacles with the candidate probability of the obstacles being greater than or equal to the preset probability as target positions of the obstacles, and marking the target positions of the obstacles in the area of the obstacle map to form the obstacle map.
Of course, the storage medium containing the computer-executable instructions provided by the embodiments of the present invention is not limited to the method operations described above, and may also perform related operations in the method for generating the obstacle map provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the obstacle map generating device, the included units and modules are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. An obstacle map generation method, comprising:
establishing an obstacle map area according to a first vehicle position at a first moment;
determining alternative positions of all obstacles and corresponding alternative probabilities of the obstacles in the obstacle map area according to the acquired radar signals of the vehicle;
and determining the candidate positions of the obstacles with the candidate probability of the obstacles being greater than or equal to the preset probability as target positions of the obstacles, and marking the target positions of the obstacles in the area of the obstacle map to form the obstacle map.
2. The obstacle map generation method according to claim 1, wherein the establishing an obstacle map area according to the vehicle position at the first time includes:
the method comprises the steps of obtaining a first vehicle position at a first moment, and determining a vehicle position area with a preset area by taking the first vehicle position as an origin;
dividing the vehicle position area into a preset number of area blocks, and determining the preset number of area blocks as an obstacle map area.
3. The method according to claim 2, wherein the determining, according to the acquired vehicle radar signal, each obstacle candidate position and a corresponding obstacle candidate probability in the obstacle map area includes:
periodically acquiring vehicle radar signals, and determining cycle alternative positions and corresponding cycle alternative probabilities of obstacle information in the vehicle radar signals aiming at the vehicle radar signals acquired each time;
and weighting and summing the cycle alternative probabilities with the same cycle alternative positions in the preset cycle number according to a preset weighting coefficient to obtain the alternative positions of the obstacles and the corresponding alternative probabilities of the obstacles.
4. The method of claim 3, wherein the determining the periodic candidate locations and corresponding periodic candidate probabilities for each obstacle information in the vehicle radar signal comprises:
determining the barrier distance between the barrier in each barrier information and the current vehicle position and the acquisition angle of the vehicle radar signal according to the vehicle radar signal;
for each piece of obstacle information, determining the region block where the point which is within the acquisition angle and away from the current vehicle position by the obstacle distance is located as a periodic alternative position;
and determining the cycle alternative probability corresponding to the cycle alternative positions according to the number of the cycle alternative positions.
5. The obstacle map generation method according to claim 3, characterized by further comprising:
and monitoring the candidate obstacle probability corresponding to each candidate obstacle position, and if the candidate obstacle probability does not change within a preset failure period number, setting the candidate obstacle probability to zero.
6. The obstacle map generation method according to claim 1, further comprising, after establishing the obstacle map area in accordance with the first vehicle position at the first time,:
acquiring a second vehicle position at a second moment, and determining the minimum distance between the second vehicle position and the edge of the obstacle map area;
and if the minimum distance is smaller than a preset critical distance, updating the obstacle map area according to the second vehicle position.
7. The method of generating an obstacle map according to claim 1, wherein before determining each obstacle candidate position and corresponding obstacle candidate probability in the obstacle map area, the method further comprises:
and filtering the vehicle radar signal.
8. An obstacle map generation device, characterized by comprising:
the map area establishing module is used for establishing an obstacle map area according to a first vehicle position at a first moment;
the alternative area probability determining module is used for determining alternative positions of all obstacles and corresponding alternative probabilities of the obstacles in the obstacle map area according to the acquired radar signals of the vehicle;
and the obstacle map forming module is used for determining the obstacle candidate position with the obstacle candidate probability greater than or equal to the preset probability as an obstacle target position, and marking the obstacle target position in the obstacle map area to form an obstacle map.
9. A vehicle, characterized in that the vehicle comprises:
one or more processors;
a memory for storing one or more programs;
a radar for collecting obstacle information around the vehicle;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the obstacle mapping method of any of claims 1-7.
10. A storage medium containing computer-executable instructions for performing the obstacle mapping method of any one of claims 1-7 when executed by a computer processor.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112578385A (en) * | 2020-11-24 | 2021-03-30 | 广州极飞科技有限公司 | Radar data processing method and device and operation equipment |
| CN112572423A (en) * | 2020-12-30 | 2021-03-30 | 广州小鹏自动驾驶科技有限公司 | Parking assisting method and device |
| CN112649013A (en) * | 2020-12-29 | 2021-04-13 | 天津天瞳威势电子科技有限公司 | Method and device for determining passable area and electronic equipment |
| CN112644480A (en) * | 2021-01-18 | 2021-04-13 | 广州小鹏自动驾驶科技有限公司 | Obstacle detection method, obstacle detection system, computer device and storage medium |
| CN112863230A (en) * | 2020-12-30 | 2021-05-28 | 上海欧菲智能车联科技有限公司 | Empty parking space detection method and device, vehicle and computer equipment |
| CN113776516A (en) * | 2021-09-03 | 2021-12-10 | 上海擎朗智能科技有限公司 | Method and device for adding obstacles, electronic equipment and storage medium |
| CN116153077A (en) * | 2023-03-31 | 2023-05-23 | 小米汽车科技有限公司 | Method, apparatus and medium for preventing transmission and display of travel information |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101371718B1 (en) * | 2011-12-01 | 2014-03-10 | 현대자동차(주) | Tracking method of vehicle's surrounding obstacles |
| KR20160048530A (en) * | 2014-10-24 | 2016-05-04 | 국방과학연구소 | Method and apparatus for generating pathe of autonomous vehicle |
| CN107000753A (en) * | 2015-03-24 | 2017-08-01 | 宝马股份公司 | Method for providing the barrier map for vehicle |
| CN108931246A (en) * | 2017-05-26 | 2018-12-04 | 杭州海康机器人技术有限公司 | A kind of method and apparatus for the barrier existing probability detecting unknown position |
| CN110045376A (en) * | 2019-04-28 | 2019-07-23 | 森思泰克河北科技有限公司 | It can travel area obtaining method, computer readable storage medium and terminal device |
| CN110703747A (en) * | 2019-10-09 | 2020-01-17 | 武汉大学 | Robot autonomous exploration method based on simplified generalized Voronoi diagram |
| CN110858076A (en) * | 2018-08-22 | 2020-03-03 | 杭州海康机器人技术有限公司 | Equipment positioning and grid map construction method and mobile robot |
| CN111089585A (en) * | 2019-12-30 | 2020-05-01 | 哈尔滨理工大学 | Mapping and positioning method based on sensor information fusion |
-
2020
- 2020-08-14 CN CN202010820959.5A patent/CN111942374A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR101371718B1 (en) * | 2011-12-01 | 2014-03-10 | 현대자동차(주) | Tracking method of vehicle's surrounding obstacles |
| KR20160048530A (en) * | 2014-10-24 | 2016-05-04 | 국방과학연구소 | Method and apparatus for generating pathe of autonomous vehicle |
| CN107000753A (en) * | 2015-03-24 | 2017-08-01 | 宝马股份公司 | Method for providing the barrier map for vehicle |
| CN108931246A (en) * | 2017-05-26 | 2018-12-04 | 杭州海康机器人技术有限公司 | A kind of method and apparatus for the barrier existing probability detecting unknown position |
| CN110858076A (en) * | 2018-08-22 | 2020-03-03 | 杭州海康机器人技术有限公司 | Equipment positioning and grid map construction method and mobile robot |
| CN110045376A (en) * | 2019-04-28 | 2019-07-23 | 森思泰克河北科技有限公司 | It can travel area obtaining method, computer readable storage medium and terminal device |
| CN110703747A (en) * | 2019-10-09 | 2020-01-17 | 武汉大学 | Robot autonomous exploration method based on simplified generalized Voronoi diagram |
| CN111089585A (en) * | 2019-12-30 | 2020-05-01 | 哈尔滨理工大学 | Mapping and positioning method based on sensor information fusion |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112578385A (en) * | 2020-11-24 | 2021-03-30 | 广州极飞科技有限公司 | Radar data processing method and device and operation equipment |
| CN112578385B (en) * | 2020-11-24 | 2023-07-18 | 广州极飞科技股份有限公司 | Radar data processing method and device and operation equipment |
| CN112649013A (en) * | 2020-12-29 | 2021-04-13 | 天津天瞳威势电子科技有限公司 | Method and device for determining passable area and electronic equipment |
| CN112572423A (en) * | 2020-12-30 | 2021-03-30 | 广州小鹏自动驾驶科技有限公司 | Parking assisting method and device |
| CN112863230A (en) * | 2020-12-30 | 2021-05-28 | 上海欧菲智能车联科技有限公司 | Empty parking space detection method and device, vehicle and computer equipment |
| CN112572423B (en) * | 2020-12-30 | 2022-08-16 | 广州小鹏自动驾驶科技有限公司 | Parking assisting method and device |
| CN112644480A (en) * | 2021-01-18 | 2021-04-13 | 广州小鹏自动驾驶科技有限公司 | Obstacle detection method, obstacle detection system, computer device and storage medium |
| CN113776516A (en) * | 2021-09-03 | 2021-12-10 | 上海擎朗智能科技有限公司 | Method and device for adding obstacles, electronic equipment and storage medium |
| CN116153077A (en) * | 2023-03-31 | 2023-05-23 | 小米汽车科技有限公司 | Method, apparatus and medium for preventing transmission and display of travel information |
| CN116153077B (en) * | 2023-03-31 | 2023-07-18 | 小米汽车科技有限公司 | Method, apparatus and medium for preventing transmission and display of travel information |
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