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公开(公告)号：US20220390591A1
公开(公告)日：2022-12-08
申请号：US17337664
申请日：2021-06-03
发明人： Yunfei Long , Daniel Morris , Xiaoming Liu , Marcos Paul Gerardo Castro , Praveen Narayanan , Punarjay Chakravarty
IPC分类号： G01S13/89 , G06T7/579 , G01S13/931 , G01B15/00
摘要： A computer includes a processor and a memory storing instructions executable by the processor to receive radar data from a radar, the radar data including radar pixels having respective measured depths; receive camera data from a camera, the camera data including an image frame including camera pixels; map the radar pixels to the image frame; generate respective regions of the image frame surrounding the respective radar pixels; for each region, determine confidence scores for the respective camera pixels in that region; output a depth map of projected depths for the respective camera pixels based on the confidence scores; and operate a vehicle including the radar and the camera based on the depth map. The confidence scores indicate confidence in applying the measured depth of the radar pixel for that region to the respective camera pixels.
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公开(公告)号：US12061253B2
公开(公告)日：2024-08-13
申请号：US17337664
申请日：2021-06-03
发明人： Yunfei Long , Daniel Morris , Xiaoming Liu , Marcos Paul Gerardo Castro , Praveen Narayanan , Punarjay Chakravarty
IPC分类号： G06T7/00 , G01B15/00 , G01S13/89 , G01S13/931 , G06T7/579
CPC分类号： G01S13/89 , G01B15/00 , G01S13/931 , G06T7/579 , G06T2207/10028 , G06T2207/20081 , G06T2207/20084 , G06T2207/30252
摘要： A computer includes a processor and a memory storing instructions executable by the processor to receive radar data from a radar, the radar data including radar pixels having respective measured depths; receive camera data from a camera, the camera data including an image frame including camera pixels; map the radar pixels to the image frame; generate respective regions of the image frame surrounding the respective radar pixels; for each region, determine confidence scores for the respective camera pixels in that region; output a depth map of projected depths for the respective camera pixels based on the confidence scores; and operate a vehicle including the radar and the camera based on the depth map. The confidence scores indicate confidence in applying the measured depth of the radar pixel for that region to the respective camera pixels.
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公开(公告)号：US20240264276A1
公开(公告)日：2024-08-08
申请号：US18423694
申请日：2024-01-26
发明人： Yunfei Long , Daniel Morris , Abhinav Kumar , Xiaoming Liu , Marcos Paul Gerardo Castro , Punarjay Chakravarty , Praveen Narayanan
IPC分类号： G01S7/41 , G01S13/86 , G01S13/89 , G01S13/931
CPC分类号： G01S7/417 , G01S13/867 , G01S13/89 , G01S2013/9318 , G01S2013/93185 , G01S2013/9319
摘要： A computer that includes a processor and a memory, the memory including instructions executable by the processor to generate radar data by projecting radar returns of objects within a scene onto an image plane of camera data of the scene based on extrinsic and intrinsic parameters of a camera and extrinsic parameters of a radar sensor to generate the radar data. The image data can be received at an image channel of an image/radar convolutional neural network (CNN) and receive the radar data at a radar channel of the image/radar CNN, wherein features are transferred from the image channel to the radar channel at multiple stages Image object features and image confidence scores can be determined by the image channel, and radar object features and radar confidences by the radar channel. The image object features can be combined with the radar object features using a weighted sum.
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公开(公告)号：US20230023347A1
公开(公告)日：2023-01-26
申请号：US17384010
申请日：2021-07-23
发明人： Xiaoming Liu , Daniel Morris , Yunfei Long , Marcos Paul Gerardo Castro , Punarjay Chakravarty , Praveen Narayanan
摘要： A computer includes a processor and a memory storing instructions executable by the processor to receive radar data including a radar pixel having a radial velocity from a radar; receive camera data including an image frame including camera pixels from a camera; map the radar pixel to the image frame; generate a region of the image frame surrounding the radar pixel; determine association scores for the respective camera pixels in the region; select a first camera pixel of the camera pixels from the region, the first camera pixel having a greatest association score of the association scores; and calculate a full velocity of the radar pixel using the radial velocity of the radar pixel and a first optical flow at the first camera pixel. The association scores indicate a likelihood that the respective camera pixels correspond to a same point in an environment as the radar pixel.
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5.发明授权公开(公告)号：US11164015B2
公开(公告)日：2021-11-02
申请号：US15974436
申请日：2018-05-08
摘要： Systems, methods, and devices for estimating a shape of an object based on sensor data and determining a presence of a fault or a failure in a perception system. A method of the disclosure includes receiving sensor data from a range sensor and calculating a current shape reconstruction of an object based on the sensor data. The method includes retrieving from memory a prior shape reconstruction of the object based on prior sensor data. The method includes calculating a quality score for the current shape reconstruction by balancing a function of resulted variances of the current shape reconstruction and a similarity between the current shape reconstruction and the prior shape reconstruction.
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公开(公告)号：US20190080184A1
公开(公告)日：2019-03-14
申请号：US16184680
申请日：2018-11-08
摘要： A system for detecting and identifying foliage includes a tracking component, a tracking parameters component, and a classification component. The tracking component is configured to detect and track one or more features within range data from one or more sensors. The tracking parameters component is configured to determine tracking parameters for each of the one or more features. The tracking parameters include a tracking age and one or more of a detection consistency and a position variability. The classification component is configured to classify a feature of the one or more features as corresponding to foliage based on the tracking parameters.
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公开(公告)号：US20180281680A1
公开(公告)日：2018-10-04
申请号：US15478118
申请日：2017-04-03
CPC分类号： B60R1/00 , B60R2300/802 , B60R2300/8093 , G01S7/4808 , G01S17/936 , G01S2013/9317 , G06F17/11 , G06N7/005
摘要： Example obstacle detection systems and methods are described. In one implementation, a method receives data from at least one sensor mounted to a vehicle and creates a probabilistic grid-based map associated with an area near the vehicle. The method also determines a confidence associated with each probability in the grid-based map and determines a likelihood that an obstacle exists in the area near the vehicle based on the probabilistic grid-based map.
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公开(公告)号：US20180126984A1
公开(公告)日：2018-05-10
申请号：US15346210
申请日：2016-11-08
摘要： A controller receives outputs form a plurality of sensors such as a camera, LIDAR sensor, RADAR sensor, and ultrasound sensor. Sensor outputs corresponding to an object are assigned to a tracklet. Subsequent outputs by any of the sensors corresponding to that object are also assigned to the tracklet. A trajectory of the object is calculated from the sensor outputs assigned to the tracklet, such as by means of Kalman filtering. For each sensor output assigned to the tracklet, a probability is updated, such as using a Bayesian probability update. When the probability meets a threshold condition, the object is determined to be present and an alert is generated or autonomous obstacle avoidance is performed with respect to an expected location of the object.
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公开(公告)号：US20230282000A1
公开(公告)日：2023-09-07
申请号：US17684509
申请日：2022-03-02
CPC分类号： G06V20/56 , G01S13/867 , G01S13/726 , G01S13/931 , G01S7/412 , G06V10/803 , B60W60/0027
摘要： At a first timestep, one or more first objects can be determined in a first fusion image based on determining one or more first radar clusters in first radar data and determining one or more first two-dimensional bounding boxes in first camera data. First detected objects and first undetected objects can be determined by inputting the first objects and the first radar clusters into a data association algorithm, which determines first probabilities and adds the first radar clusters and the first objects to one or more of first detected objects or first undetected objects by determining a cost function. The first detected objects and the first undetected objects can be input to a first Poisson multi-Bernoulli mixture (PMBM) filter to determine second detected objects, second undetected objects and second probabilities. The second detected objects and the second undetected objects can be reduced based on the second probabilities determined by the first PMBM filter and the second detected objects can be output.
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公开(公告)号：US10315649B2
公开(公告)日：2019-06-11
申请号：US15363763
申请日：2016-11-29
发明人： Sneha Kadetotad , Jinesh J. Jain , Vidya Nariyambut Murali , Dongran Liu , Marcos Paul Gerardo Castro , Adil Nizam Siddiqui
摘要： A controller receives outputs from a plurality of sensors such as a camera, LIDAR sensor, RADAR sensor, and ultrasound sensor, which may be rearward facing. A probability is updated each time a feature in a sensor output indicates presence of an object. The probability may be updated as a function of a variance of the sensor providing the output and a distance to the feature. Where the variance of a sensor is directional, directional probabilities may be updated according to these variances and the distance to the feature. If the probability meets a threshold condition, actions may be taken such as a perceptible alert or automatic braking. The probability may be decayed in the absence of detection of objects. Increasing or decreasing trends in the probability may be amplified by further increasing or decreasing the probability.
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