WO2021223116A1 - 感知地图生成方法、装置、计算机设备和存储介质 - Google Patents
感知地图生成方法、装置、计算机设备和存储介质 Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/28—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network with correlation of data from several navigational instruments
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- the target recognition module is used to perform target recognition on the initial image to obtain obstacle information
- a method for generating a perception map is provided. Taking the method applied to the vehicle terminal in FIG. 1 as an example for description, the method includes the following steps:
- the method further includes: obtaining the speed, driving direction, and current time of the vehicle; obtaining the first perception map according to the current time and the timestamp of the initial perception map 1.
- Compensation time Based on the vehicle's speed, driving direction and compensation time, dead-reckoning is performed on the vehicle position to obtain the vehicle's position in the initial perception map. In the foregoing embodiment, taking into account the time required for vehicle driving and data processing, the vehicle position in the initial perception map is compensated, which can ensure the accuracy of the initial perception map.
- back-projecting the location information and obstacle information to the initial perception map includes: obtaining the timestamp of the initial perception map; calculating and calculating according to the timestamp of the location information and the timestamp of the obstacle information respectively The second compensation time between the timestamps of the initial perception map; the location information and obstacle information are compensated according to the second compensation time; the location information and obstacle information after the dead location compensation are back-projected to the initial perception In the map.
- the issue of the running speed of each data processing process is fully considered, and dead-reckoning is performed by processing the time stamp information of the image, which can ensure the accuracy of the subsequent target perception map.
- the above-mentioned target perception map is generally obtained during the driving process of the vehicle. Therefore, in order to improve the accuracy of data processing, the vehicle terminal is based on the Bayesian probability density model as the main update strategy of the map, and the confidence of the perception result is respectively determined. The information is updated cumulatively to ensure the accuracy and reliability of the perception of obstacles on the map during operation.
- the vehicle terminal can also perform location recognition on the initial image and the corresponding ring view to obtain the location probability map, and perform target recognition on the initial image in turn to obtain the obstacle probability map.
- the library can be obtained based on the target probability and the location probability map.
- Position information; Obstacle information is obtained based on the target probability and the obstacle probability map, that is, the information processed in the previous frame is superimposed to prevent processing errors caused by missed detection and false detection, and improve processing accuracy.
- the embedded real-time online perception map construction scheme based on the on-board surround view system and dead reckoning is given, which can collect information about the surrounding body of the car in different scenarios to obtain a reliable target perception map, thereby ensuring higher-level functional expansion , Such as the reliability and convenience of the realization of APA and AVP functions.
- the location identification module 300 is used to identify the location of the initial image and the corresponding ring view to obtain location information
- performing semantic segmentation processing on the generated ring views in sequence after obtaining the initial perception map further includes: obtaining the speed, driving direction, and current time of the vehicle ; Obtain the first compensation time according to the current time and the timestamp of the initial perception map; perform dead-reckoning on the vehicle position based on the vehicle's speed, driving direction and compensation time to obtain the position of the vehicle in the initial perception map.
- back-projecting the location information and obstacle information to the initial perception map includes: obtaining the timestamp of the initial perception map; The second compensation time between the time stamp of the information, the time stamp of the obstacle information and the time stamp of the initial perception map; the dead-reckoning is performed on the location information and the obstacle information according to the second compensation time; after the dead-reckoning The location information and obstacle information of the data are back-projected to the initial perception map.
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Abstract
Description
Claims (20)
- 一种感知地图生成方法,包括:采集车辆周围的初始图像,并根据多张所述初始图像生成环视图;对所述环视图进行语义分割处理得到初始感知地图,所述初始感知地图包括可通行区域和障碍物区域;对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,对所述初始图像进行目标识别得到障碍物信息;及将所述库位信息和所述障碍物信息反投影至所述初始感知地图中,以对所述初始感知地图中的可通行区域和障碍物区域进行调整,得到目标感知地图。
- 根据权利要求1所述的方法,其特征在于,所述初始图像携带有拍摄时间戳,所述根据多张所述初始图像生成环视图,包括:依次获取所述拍摄时间戳相对应的多张所述初始图像,并生成环视图,所述环视图的时间戳与所述初始图像的时间戳相对应。
- 根据权利要求2所述的方法,其特征在于,所述对所述环视图进行语义分割处理得到初始感知地图,包括:依次对所生成的所述环视图进行语义分割处理得到初始感知地图,所述初始感知地图的时间戳与所述环视图的时间戳对应;及所述对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,对所述初始图像进行目标识别得到障碍物信息,包括:依次对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,依次对所述初始图像进行目标识别得到障碍物信息,所述库位信息和所述障碍物信息的时间戳与所述初始图像的时间戳对应。
- 根据权利要求3所述的方法,其特征在于,所述依次对所生成的所述环视图进行语义分割处理得到初始感知地图之后,还包括:获取车辆的速度、行驶方向以及当前时间;根据所述当前时间和所述初始感知地图的时间戳得到第一补偿时间;及基于所述车辆的速度、行驶方向以及所述补偿时间对车辆位置进行航位补偿得到车辆在所述初始感知地图中的位置。
- 根据权利要求3所述的方法,其特征在于,所述将所述库位信息和所述障碍物信息反投影至所述初始感知地图中,包括:获取所述初始感知地图的时间戳;分别根据所述库位信息的时间戳、所述障碍物信息的时间戳计算与所述初始感知地图的时间戳之间的第二补偿时间;根据所述第二补偿时间对所述库位信息和障碍物信息进行航位补偿;及将航位补偿后的所述库位信息和所述障碍物信息反投影至所述初始感知地图中。
- 根据权利要求3所述的方法,其特征在于,所述依次对所生成的所述环视图进行语义分割处理得到初始感知地图,包括:依次对所生成的所述环视图进行语义分割处理得到初始概率图;获取上一目标感知地图对应的目标概率;及基于所述初始概率图以及所述目标概率得到初始感知地图,所述初始感知地图包括可通行区域和障碍物区域的概率。
- 根据权利要求3所述的方法,其特征在于,所述依次对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,依次对所述初始图像进行目标识别得到障碍物信息,包括:依次对所述初始图像和以及对应的所述环视图进行库位识别得到库位概率图,依次对所述初始图像进行目标识别得到障碍物概率图;基于所述目标概率以及所述库位概率图得到库位信息;及基于所述目标概率以及所述障碍物概率图得到障碍物信息。
- 根据权利要求1至7任意一项所述的方法,其特征在于,所述对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,包括:对所述初始图像和以及对应的所述环视图进行库位识别得到库位特征;获取预设库位判断逻辑;及通过所述预设库位判断逻辑对所述库位特征进行判断得到库位信息。
- 一种感知地图生成装置,其特征在于,所述装置包括:采集模块,用于采集车辆周围的初始图像,并根据多张所述初始图像生成环视图;语义分割模块,用于对所述环视图进行语义分割处理得到初始感知地图,所述初始感知地图包括可通行区域和障碍物区域;库位识别模块,用于对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息;目标识别模块,用于对所述初始图像进行目标识别得到障碍物信息;感知地图生成模块,用于将所述库位信息和所述障碍物信息反投影至所述初始感知地图中,以对所述初始感知地图中的可通行区域和障碍物区域进行调整,得到目标感知地图。
- 根据权利要求9所述的装置,其特征在于,所述采集模块还用于依次获取所述拍摄时间戳相对应的多张所述初始图像,并生成环视图,所述环视图的时间戳与所述初始图像的时间戳相对应。
- 一种计算机设备,包括存储器及一个或多个处理器,所述存储器中储存有计算机可读指令,所述计算机可读指令被所述一个或多个处理器执行时,使得所述一个或多个处理器执行以下步骤:采集车辆周围的初始图像,并根据多张所述初始图像生成环视图;对所述环视图进行语义分割处理得到初始感知地图,所述初始感知地图包括可通行区 域和障碍物区域;对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,对所述初始图像进行目标识别得到障碍物信息;及将所述库位信息和所述障碍物信息反投影至所述初始感知地图中,以对所述初始感知地图中的可通行区域和障碍物区域进行调整,得到目标感知地图。
- 根据权利要求11所述的计算机设备,其特征在于,所述处理器执行所述计算机可读指令时所实现的所述初始图像携带有拍摄时间戳,所述根据多张所述初始图像生成环视图,包括:依次获取所述拍摄时间戳相对应的多张所述初始图像,并生成环视图,所述环视图的时间戳与所述初始图像的时间戳相对应。
- 根据权利要求12所述的计算机设备,其特征在于,所述处理器执行所述计算机可读指令时所实现的所述对所述环视图进行语义分割处理得到初始感知地图,包括:依次对所生成的所述环视图进行语义分割处理得到初始感知地图,所述初始感知地图的时间戳与所述环视图的时间戳对应;及所述对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,对所述初始图像进行目标识别得到障碍物信息,包括:依次对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,依次对所述初始图像进行目标识别得到障碍物信息,所述库位信息和所述障碍物信息的时间戳与所述初始图像的时间戳对应。
- 根据权利要求13所述的计算机设备,其特征在于,所述处理器执行所述计算机可读指令时所实现的所述依次对所生成的所述环视图进行语义分割处理得到初始感知地图之后,还包括:获取车辆的速度、行驶方向以及当前时间;根据所述当前时间和所述初始感知地图的时间戳得到第一补偿时间;及基于所述车辆的速度、行驶方向以及所述补偿时间对车辆位置进行航位补偿得到车辆在所述初始感知地图中的位置。
- 根据权利要求13所述的计算机设备,其特征在于,所述处理器执行所述计算机可读指令时所实现的所述将所述库位信息和所述障碍物信息反投影至所述初始感知地图中,包括:获取所述初始感知地图的时间戳;分别根据所述库位信息的时间戳、所述障碍物信息的时间戳计算与所述初始感知地图的时间戳之间的第二补偿时间;根据所述第二补偿时间对所述库位信息和障碍物信息进行航位补偿;及将航位补偿后的所述库位信息和所述障碍物信息反投影至所述初始感知地图中。
- 根据权利要求13所述的计算机设备,其特征在于,所述处理器执行所述计算机 可读指令时所实现的所述依次对所生成的所述环视图进行语义分割处理得到初始感知地图,包括:依次对所生成的所述环视图进行语义分割处理得到初始概率图;获取上一目标感知地图对应的目标概率;及基于所述初始概率图以及所述目标概率得到初始感知地图,所述初始感知地图包括可通行区域和障碍物区域的概率。
- 根据权利要求13所述的计算机设备,其特征在于,所述处理器执行所述计算机可读指令时所实现的所述依次对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,依次对所述初始图像进行目标识别得到障碍物信息,包括:依次对所述初始图像和以及对应的所述环视图进行库位识别得到库位概率图,依次对所述初始图像进行目标识别得到障碍物概率图;基于所述目标概率以及所述库位概率图得到库位信息;及基于所述目标概率以及所述障碍物概率图得到障碍物信息。
- 根据权利要求11至17任意一项所述的计算机设备,其特征在于,所述处理器执行所述计算机可读指令时所实现的所述对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,包括:对所述初始图像和以及对应的所述环视图进行库位识别得到库位特征;获取预设库位判断逻辑;及通过所述预设库位判断逻辑对所述库位特征进行判断得到库位信息。
- 一个或多个存储有计算机可读指令的非易失性计算机可读存储介质,所述计算机可读指令被一个或多个处理器执行时,使得所述一个或多个处理器执行以下步骤:采集车辆周围的初始图像,并根据多张所述初始图像生成环视图;对所述环视图进行语义分割处理得到初始感知地图,所述初始感知地图包括可通行区域和障碍物区域;对所述初始图像和以及对应的所述环视图进行库位识别得到库位信息,对所述初始图像进行目标识别得到障碍物信息;及将所述库位信息和所述障碍物信息反投影至所述初始感知地图中,以对所述初始感知地图中的可通行区域和障碍物区域进行调整,得到目标感知地图。
- 根据权利要求19所述的存储介质,其特征在于,所述计算机可读指令被所述处理器执行时所实现的所述初始图像携带有拍摄时间戳,所述根据多张所述初始图像生成环视图,包括:依次获取所述拍摄时间戳相对应的多张所述初始图像,并生成环视图,所述环视图的时间戳与所述初始图像的时间戳相对应。
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