Patents by Inventor Miguel Sainz
Miguel Sainz 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: 11874663Abstract: A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.Type: GrantFiled: August 26, 2022Date of Patent: January 16, 2024Assignee: NVIDIA CorporationInventors: Gary Hicok, Michael Cox, Miguel Sainz, Martin Hempel, Ratin Kumar, Timo Roman, Gordon Grigor, David Nister, Justin Ebert, Chin-Hsien Shih, Tony Tam, Ruchi Bhargava
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Publication number: 20230267701Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.Type: ApplicationFiled: May 1, 2023Publication date: August 24, 2023Inventors: Yifang Xu, Xin Liu, Chia-Chin Chen, Carolina Parada, Davide Onofrio, Minwoo Park, Mehdi Sajjadi Mohammadabadi, Vijay Chintalapudi, Ozan Tonkal, John Zedlewski, Pekka Janis, Jan Nikolaus Fritsch, Gordon Grigor, Zuoguan Wang, I-Kuei Chen, Miguel Sainz
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Patent number: 11676364Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.Type: GrantFiled: April 5, 2021Date of Patent: June 13, 2023Assignee: NVIDIA CorporationInventors: Yifang Xu, Xin Liu, Chia-Chih Chen, Carolina Parada, Davide Onofrio, Minwoo Park, Mehdi Sajjadi Mohammadabadi, Vijay Chintalapudi, Ozan Tonkal, John Zedlewski, Pekka Janis, Jan Nikolaus Fritsch, Gordon Grigor, Zuoguan Wang, I-Kuei Chen, Miguel Sainz
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Publication number: 20230130814Abstract: In examples, autonomous vehicles are enabled to negotiate yield scenarios in a safe and predictable manner. In response to detecting a yield scenario, a wait element data structure is generated that encodes geometries of an ego path, a contender path that includes at least one contention point with the ego path, as well as a state of contention associated with the at least on contention point. Geometry of yield scenario context may also be encoded, such as inside ground of an intersection, entry or exit lines, etc. The wait element data structure is passed to a yield planner of the autonomous vehicle. The yield planner determines a yielding behavior for the autonomous vehicle based at least on the wait element data structure. A control system of the autonomous vehicle may operate the autonomous vehicle in accordance with the yield behavior, such that the autonomous vehicle safely negotiates the yield scenario.Type: ApplicationFiled: October 27, 2021Publication date: April 27, 2023Inventors: David Nister, Minwoo Park, Miguel Sainz Serra, Vaibhav Thukral, Berta Rodriguez Hervas
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Publication number: 20220413497Abstract: A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.Type: ApplicationFiled: August 26, 2022Publication date: December 29, 2022Inventors: Gary HICOK, Michael COX, Miguel SAINZ, Martin HEMPEL, Ratin KUMAR, Timo ROMAN, Gordon GRIGOR, David NISTER, Justin EBERT, Chin-Hsien SHIH, Tony TAM, Ruchi BHARGAVA
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Patent number: 11474519Abstract: A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.Type: GrantFiled: February 26, 2019Date of Patent: October 18, 2022Assignee: NVIDIA CorporationInventors: Gary Hicok, Michael Cox, Miguel Sainz, Martin Hempel, Ratin Kumar, Timo Roman, Gordon Grigor, David Nister, Justin Ebert, Chin Shih, Tony Tam, Ruchi Bhargava
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Publication number: 20210253128Abstract: Embodiments of the present disclosure relate to behavior planning for autonomous vehicles. The technology described herein selects a preferred trajectory for an autonomous vehicle based on an evaluation of multiple hypothetical trajectories by different components within a planning system. The various components provide an optimization score for each trajectory according to the priorities of the component and scores from multiple components may form a final optimization score. This scoring system allows the competing priorities (e.g., comfort, minimal travel time, fuel economy) of different components to be considered together. In examples, the trajectory with the best combined score may be selected for implementation. As such, an iterative approach that evaluates various factors may be used to identify an optimal or preferred trajectory for an autonomous vehicle when navigating an environment.Type: ApplicationFiled: February 18, 2021Publication date: August 19, 2021Inventors: David Nister, Yizhou Wang, Julia Ng, Rotem Aviv, Seungho Lee, Joshua John Bialkowski, Hon Leung Lee, Hermes Lanker, Raul Correal Tezanos, Zhenyi Zhang, Nikolai Smolyanskiy, Alexey Kamenev, Ollin Boer Bohan, Anton Vorontsov, Miguel Sainz Serra, Birgit Henke
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Publication number: 20210241004Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.Type: ApplicationFiled: April 19, 2021Publication date: August 5, 2021Inventors: Josh Abbott, Miguel Sainz Serra, Zhaoting Ye, David Nister
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Publication number: 20210241005Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.Type: ApplicationFiled: April 19, 2021Publication date: August 5, 2021Inventors: Josh Abbott, Miguel Sainz Serra, Zhaoting Ye, David Nister
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Publication number: 20210224556Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.Type: ApplicationFiled: April 5, 2021Publication date: July 22, 2021Inventors: Yifang Xu, Xin Liu, Chia-Chih Chen, Carolina Parada, Davide Onofrio, Minwoo Park, Mehdi Sajjadi Mohammadabadi, Vijay Chintalapudi, Ozan Tonkal, John Zedlewski, Pekka Janis, Jan Nikolaus Fritsch, Gordon Grigor, Zuoguan Wang, I-Kuei Chen, Miguel Sainz
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Patent number: 10997435Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.Type: GrantFiled: August 8, 2019Date of Patent: May 4, 2021Assignee: NVIDIA CorporationInventors: Josh Abbott, Miguel Sainz Serra, Zhaoting Ye, David Nister
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Patent number: 10997433Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.Type: GrantFiled: February 26, 2019Date of Patent: May 4, 2021Assignee: NVIDIA CorporationInventors: Yifang Xu, Xin Liu, Chia-Chih Chen, Carolina Parada, Davide Onofrio, Minwoo Park, Mehdi Sajjadi Mohammadabadi, Vijay Chintalapudi, Ozan Tonkal, John Zedlewski, Pekka Janis, Jan Nikolaus Fritsch, Gordon Grigor, Zuoguan Wang, I-Kuei Chen, Miguel Sainz
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Publication number: 20210042535Abstract: In various examples, object fence corresponding to objects detected by an ego-vehicle may be used to determine overlap of the object fences with lanes on a driving surface. A lane mask may be generated corresponding to the lanes on the driving surface, and the object fences may be compared to the lanes of the lane mask to determine the overlap. Where an object fence is located in more than one lane, a boundary scoring approach may be used to determine a ratio of overlap of the boundary fence, and thus the object, with each of the lanes. The overlap with one or more lanes for each object may be used to determine lane assignments for the objects, and the lane assignments may be used by the ego-vehicle to determine a path or trajectory along the driving surface.Type: ApplicationFiled: August 8, 2019Publication date: February 11, 2021Inventors: Josh Abbott, Miguel Sainz Serra, Zhaoting Ye, David Nister
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Publication number: 20190265703Abstract: A system and method for an on-demand shuttle, bus, or taxi service able to operate on private and public roads provides situational awareness and confidence displays. The shuttle may include ISO 26262 Level 4 or Level 5 functionality and can vary the route dynamically on-demand, and/or follow a predefined route or virtual rail. The shuttle is able to stop at any predetermined station along the route. The system allows passengers to request rides and interact with the system via a variety of interfaces, including without limitation a mobile device, desktop computer, or kiosks. Each shuttle preferably includes an in-vehicle controller, which preferably is an AI Supercomputer designed and optimized for autonomous vehicle functionality, with computer vision, deep learning, and real time ray tracing accelerators. An AI Dispatcher performs AI simulations to optimize system performance according to operator-specified system parameters.Type: ApplicationFiled: February 26, 2019Publication date: August 29, 2019Inventors: Gary HICOK, Michael COX, Miguel SAINZ, Martin HEMPEL, Ratin KUMAR, Timo ROMAN, Gordon GRIGOR, David NISTER, Justin EBERT, Chin SHIH, Tony TAM, Ruchi BHARGAVA
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Publication number: 20190266418Abstract: In various examples, sensor data representative of an image of a field of view of a vehicle sensor may be received and the sensor data may be applied to a machine learning model. The machine learning model may compute a segmentation mask representative of portions of the image corresponding to lane markings of the driving surface of the vehicle. Analysis of the segmentation mask may be performed to determine lane marking types, and lane boundaries may be generated by performing curve fitting on the lane markings corresponding to each of the lane marking types. The data representative of the lane boundaries may then be sent to a component of the vehicle for use in navigating the vehicle through the driving surface.Type: ApplicationFiled: February 26, 2019Publication date: August 29, 2019Inventors: Yifang Xu, Xin Liu, Chia-Chih Chen, Carolina Parada, Davide Onofrio, Minwoo Park, Mehdi Sajjadi Mohammadabadi, Vijay Chintalapudi, Ozan Tonkal, John Zedlewski, Pekka Janis, Jan Nikolaus Fritsch, Gordon Grigor, Zuoguan Wang, I-Kuei Chen, Miguel Sainz
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Patent number: 8947430Abstract: A method for rendering a particle-based fluid surface includes generating a depth image of a plurality of particles which form a fluid surface, and smoothing the depth image to generate a smoothed depth image. From the smoothed depth image, a smoothed surface position and a smoothed surface normal for each of a plurality of pixels included within the smoothed depth image is determined, and a shaded surface of the fluid is rendered as a function of the smoothed surface positions and the smoothed surface normals.Type: GrantFiled: February 26, 2010Date of Patent: February 3, 2015Assignee: NVIDIA CorporationInventors: Simon Green, Miguel Sainz, Wladimir Van Der Laan
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Publication number: 20140368505Abstract: A graphics processing subsystem for recovering projection parameters for rendering effects and a method of use thereof. One embodiment of the graphics processing subsystem includes: (1) a memory configured to store a buffer having a plurality of constants determinable upon execution of an application for which a scene is rendered, and (2) a central processing unit (CPU) operable to determine projection parameters from the buffer according to shader-reflection metadata attached to a programmable shader submitted for execution, and employ the projection parameters to cause an effect to be rendered on the scene by a graphics processing unit (GPU).Type: ApplicationFiled: June 13, 2013Publication date: December 18, 2014Inventors: Louis Bavoil, Miguel Sainz, Byungmoon Kim
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Patent number: 8878849Abstract: The method includes receiving a plurality of graphics primitives for rendering at a GPU of a computer system and rendering graphics primitives into pixel parameters of the pixels of a display, wherein the parameters include pixel depth values and pixel normal values. For each pixel of the display, an ambient occlusion process is performed. The algorithm takes as input a ND-buffer containing pixel depth values and pixel normals. Based on the pixel 3-D position and the pixel normal vector, horizon heights are computed by sampling the ND-buffer and an occlusion term is computed for each pixel based on the horizon heights. Based on the pixel 3-D position, the pixel normal vector, a normal occlusion term is computed by sampling the ND-buffer above the horizon in multiple directions. An ambient occlusion illumination value is computed by combining the horizon occlusion term and the normal occlusion term.Type: GrantFiled: December 14, 2007Date of Patent: November 4, 2014Assignee: Nvidia CorporationInventors: Rouslan Dimitrov, Louis Bavoil, Miguel Sainz
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Publication number: 20140160124Abstract: A visible polygon data structure and method of use thereof. One embodiment of the visible polygon data structure includes: (1) a memory configured to store a data structure containing vertices of at least partially visible polygons of the scene but lacking vertices of at least some wholly invisible polygons of the scene, and (2) a graphics processing unit (GPU) configured to employ the vertices of the at least partially visible polygons to approximate an ambient occlusive effect on a point in the scene, the effect being independent of the wholly invisible polygons.Type: ApplicationFiled: December 12, 2012Publication date: June 12, 2014Applicant: NVIDIA CORPORATIONInventors: Louis Bavoil, Miguel Sainz
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Publication number: 20090153557Abstract: The method includes receiving a plurality of graphics primitives for rendering at a GPU of a computer system and rendering graphics primitives into pixel parameters of the pixels of a display, wherein the parameters include pixel depth values and pixel normal values. For each pixel of the display, an ambient occlusion process is performed. The algorithm takes as input a ND-buffer containing pixel depth values and pixel normals. Based on the pixel 3-D position and the pixel normal vector, horizon heights are computed by sampling the ND-buffer and an occlusion term is computed for each pixel based on the horizon heights. Based on the pixel 3-D position, the pixel normal vector, a normal occlusion term is computed by sampling the ND-buffer above the horizon in multiple directions. An ambient occlusion illumination value is computed by combining the horizon occlusion term and the normal occlusion term.Type: ApplicationFiled: December 14, 2007Publication date: June 18, 2009Inventors: Rouslan Dimitrov, Louis Bavoil, Miguel Sainz