Patents by Inventor Marcos Paul Gerardo Castro
Marcos Paul Gerardo Castro has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Patent number: 12061253Abstract: 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.Type: GrantFiled: June 3, 2021Date of Patent: August 13, 2024Assignees: Ford Global Technologies, LLC, Board of Trustees of Michigan State UniversityInventors: Yunfei Long, Daniel Morris, Xiaoming Liu, Marcos Paul Gerardo Castro, Praveen Narayanan, Punarjay Chakravarty
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Publication number: 20240264276Abstract: 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.Type: ApplicationFiled: January 26, 2024Publication date: August 8, 2024Applicants: Ford Global Technologies, LLC, Board of Trustees of Michigan State UniversityInventors: Yunfei Long, Daniel Morris, Abhinav Kumar, Xiaoming Liu, Marcos Paul Gerardo Castro, Punarjay Chakravarty, Praveen Narayanan
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Patent number: 12039783Abstract: 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.Type: GrantFiled: September 30, 2021Date of Patent: July 16, 2024Assignee: Ford Global Technologies, LLCInventors: Marcos Paul Gerardo Castro, Jinesh Jain, Bruno Sielly Jales Costa
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Publication number: 20240144663Abstract: A system is disclosed that includes a computer that includes a processor and a memory, the memory including instructions executable by the processor to input an image acquired by a sensor to a neural network to output a prediction regarding an object included in the image. The neural network can be trained, based on (a) a distributed robust optimization that minimizes an expectation applied to probability distributions of loss functions to select training images that yield a solution with a selected uncertainty level and (b) generating additional input images based on adversarial images.Type: ApplicationFiled: November 1, 2022Publication date: May 2, 2024Applicants: Ford Global Technologies, LLC, The Board of Trustees of the Leland Stanford Junior UniversityInventors: Xinru Hua, Huanzhong Xu, Jose Blanchet, Viet Anh Nguyen, Marcos Paul Gerardo Castro
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Publication number: 20240094384Abstract: Tracking an object included in a reflective surface by detecting the reflective surface included in one or more images included in a plurality of images by determining a location of the reflective surface in pixel coordinates and tracking the location of the reflective surface in the plurality of images. Real world locations of the object can be determined based on attributes of the reflective surface including a geometric class, extrinsic properties that relate the reflective surface to an environment, intrinsic properties describing the reflective surface without referring to the environment and calibration properties of the sensor.Type: ApplicationFiled: September 15, 2022Publication date: March 21, 2024Applicant: Ford Global Technologies, LLCInventors: Marcos Paul Gerardo Castro, Aniruddh Ravindran, Mishel Johns
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Publication number: 20230282000Abstract: 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.Type: ApplicationFiled: March 2, 2022Publication date: September 7, 2023Applicant: Ford Global Technologies, LLCInventors: Su Pang, Marcos Paul Gerardo Castro, Jinhyoung Oh, Clifton K. Thomas, Jinesh Jain
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Patent number: 11698437Abstract: A system can include a computer including a processor and a memory, the memory storing instructions executable by the processor to receive point cloud data. The instructions further include instructions to generate a plurality of feature maps based on the point cloud data, each feature map of the plurality of feature maps corresponding to a parameter of the point cloud data. The instructions further include instructions to aggregate the plurality of feature maps into an aggregated feature map. The instructions further include instructions to generate, via a feedforward neural network, at least one of a segmentation output or a classification output based on the aggregated feature map.Type: GrantFiled: September 1, 2020Date of Patent: July 11, 2023Assignee: FORD GLOBAL TECHNOLOGIES, LLCInventors: Marcos Paul Gerardo Castro, Feng Jin, Jinesh Jain
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Patent number: 11586862Abstract: A computer includes a processor and a memory storing instructions executable by the processor to collect a plurality of data sets, each data set from a respective sensor in a plurality of sensors, and each data set including a range, an azimuth angle, and a range rate for a detection point of the respective one of the sensors on an object to determine, for each detection point, a radial component of a ground speed of the detection point based on the data set associated with the detection point and a speed of a vehicle, and to generate a plurality of clusters, each cluster including selected detection points within a distance threshold from each other and having respective radial components of ground speeds that are (1) above a first threshold and (2) within a second threshold of each other.Type: GrantFiled: February 14, 2020Date of Patent: February 21, 2023Assignee: Ford Global Technologies, LLCInventors: Marcos Paul Gerardo Castro, Jinhyoung Oh, Jinesh Jain
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Publication number: 20230023347Abstract: 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.Type: ApplicationFiled: July 23, 2021Publication date: January 26, 2023Applicants: Ford Global Technologies, LLC, Board of Trustees of Michigan State UniversityInventors: Xiaoming Liu, Daniel Morris, Yunfei Long, Marcos Paul Gerardo Castro, Punarjay Chakravarty, Praveen Narayanan
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Publication number: 20220390591Abstract: 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.Type: ApplicationFiled: June 3, 2021Publication date: December 8, 2022Applicants: Ford Global Technologies, LLC, Board of Trustees of Michigan State UniversityInventors: Yunfei Long, Daniel Morris, Xiaoming Liu, Marcos Paul Gerardo Castro, Praveen Narayanan, Punarjay Chakravarty
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Publication number: 20220065992Abstract: A system can include a computer including a processor and a memory, the memory storing instructions executable by the processor to receive point cloud data. The instructions further include instructions to generate a plurality of feature maps based on the point cloud data, each feature map of the plurality of feature maps corresponding to a parameter of the point cloud data. The instructions further include instructions to aggregate the plurality of feature maps into an aggregated feature map. The instructions further include instructions to generate, via a feedforward neural network, at least one of a segmentation output or a classification output based on the aggregated feature map.Type: ApplicationFiled: September 1, 2020Publication date: March 3, 2022Applicant: Ford Global Technologies, LLCInventors: Marcos Paul GERARDO CASTRO, Feng Jin, Jinesh Jain
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Publication number: 20220027653Abstract: 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.Type: ApplicationFiled: September 30, 2021Publication date: January 27, 2022Inventors: Marcos Paul Gerardo Castro, Jinesh Jain, Bruno Sielly Jales Costa
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Patent number: 11220259Abstract: 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.Type: GrantFiled: May 1, 2019Date of Patent: January 11, 2022Assignee: FORD GLOBAL TECHNOLOGIES, LLCInventors: Sneha Kadetotad, Jinesh J Jain, Vidya Nariyambut Murali, Dongran Liu, Marcos Paul Gerardo Castro, Adil Nizam Siddiqui
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Patent number: 11164015Abstract: 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.Type: GrantFiled: May 8, 2018Date of Patent: November 2, 2021Assignee: Ford Global Technologies, LLCInventors: Marcos Paul Gerardo Castro, Jinesh Jain, Bruno Sielly Jales Costa
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Publication number: 20210300356Abstract: A computer, including a processor and a memory, the memory including instructions to be executed by the processor to, based on sensor data in a vehicle, determine a database that includes object data for a plurality of objects, including, for each object, an object identification, a measurement of one or more object attributes, and an uncertainty specifying a probability of correct object identification, for the object identification and the object attributes determined based on the sensor data, wherein the object attributes include an object size, an object shape and an object location. The instructions include further instructions to determine a map based on the database including the respective locations and corresponding uncertainties for the vehicle type and download the map to a vehicle based on the vehicle location and the vehicle type.Type: ApplicationFiled: March 25, 2020Publication date: September 30, 2021Applicant: Ford Global Technologies, LLCInventors: Shreyasha Paudel, Marcos Paul Gerardo Castro, Sandhya Bhaskar, Clifton K. Thomas
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Publication number: 20210256321Abstract: A computer includes a processor and a memory storing instructions executable by the processor to collect a plurality of data sets, each data set from a respective sensor in a plurality of sensors, and each data set including a range, an azimuth angle, and a range rate for a detection point of the respective one of the sensors on an object to determine, for each detection point, a radial component of a ground speed of the detection point based on the data set associated with the detection point and a speed of a vehicle, and to generate a plurality of clusters, each cluster including selected detection points within a distance threshold from each other and having respective radial components of ground speeds that are (1) above a first threshold and (2) within a second threshold of each other.Type: ApplicationFiled: February 14, 2020Publication date: August 19, 2021Applicant: Ford Global Technologies, LLCInventors: Marcos Paul Gerardo Castro, Jinhyoung Oh, Jinesh Jain
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Patent number: 10521680Abstract: 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.Type: GrantFiled: November 8, 2018Date of Patent: December 31, 2019Assignee: FORD GLOBAL TECHNOLOGIES, LLCInventors: Marcos Paul Gerardo Castro, Sneha Kadetotad, Dongran Liu, Jinesh J Jain
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Publication number: 20190347494Abstract: 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.Type: ApplicationFiled: May 8, 2018Publication date: November 14, 2019Inventors: Marcos Paul Gerardo Castro, Jinesh Jain, Bruno Sielly Jales Costa
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Publication number: 20190256089Abstract: 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.Type: ApplicationFiled: May 1, 2019Publication date: August 22, 2019Inventors: Sneha Kadetotad, Jinesh J. Jain, Vidya Nariyambut Murali, Dongran Liu, Marcos Paul Gerardo Castro, Adil Nizam Siddiqui
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Patent number: 10315649Abstract: 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.Type: GrantFiled: November 29, 2016Date of Patent: June 11, 2019Assignee: FORD GLOBAL TECHNOLOGIES, LLCInventors: Sneha Kadetotad, Jinesh J. Jain, Vidya Nariyambut Murali, Dongran Liu, Marcos Paul Gerardo Castro, Adil Nizam Siddiqui