Patents by Inventor Sravan Puttagunta

Sravan Puttagunta 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).

  • Publication number: 20230334850
    Abstract: Embodiments of architecture, systems, and methods used to provide map data, sensor data, and asset signature data including location data, depth data, and positional data for a terrestrially mobile entity, location and positional data for pseudo-fixed assets and dynamic assets relative to the terrestrially mobile entity via a combination of aerial sensor data and terrestrial data. Other embodiments may be described and claimed.
    Type: Application
    Filed: March 23, 2020
    Publication date: October 19, 2023
    Inventors: Scott Harvey, Sravan Puttagunta
  • Publication number: 20220188973
    Abstract: A method of augmenting camera devices with neural networks to control framerate, time synchronization, image stitching and resolution, the method comprising: creating synthetic camera frames by using neural networks to interpolate between actual frame captures; utilizing frame interpolation to align camera images when the frames are misaligned in time, with additional hardware; retroactively processing recorded sensor data to achieve time synchronization from multiple camera sensors; stitching temporally misaligned camera recordings together to create spherical or panoramic images with vision pipelines augmented by neural networks; and enhance images by utilizing neural networks to adjust optimize resolution.
    Type: Application
    Filed: December 14, 2021
    Publication date: June 16, 2022
    Inventor: Sravan Puttagunta
  • Patent number: 10549768
    Abstract: Methods and apparatus for real time machine vision and point-cloud data analysis are provided, for remote sensing and vehicle control. Point cloud data can be analyzed via scalable, centralized, cloud computing systems for extraction of asset information and generation of semantic maps. Machine learning components can optimize data analysis mechanisms to improve asset and feature extraction from sensor data. Optimized data analysis mechanisms can be downloaded to vehicles for use in on-board systems analyzing vehicle sensor data. Semantic map data can be used locally in vehicles, along with onboard sensors, to derive precise vehicle localization and provide input to vehicle to control systems.
    Type: Grant
    Filed: October 23, 2017
    Date of Patent: February 4, 2020
    Assignee: SOLFICE RESEARCH, INC.
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Anuj Gupta, Scott Harvey, Jason Creadore, Graham Mills
  • Patent number: 10489650
    Abstract: Systems and methods for providing vehicle cognition through localization and semantic mapping are provided. Localization may involve in vehicle calculation of voxel signatures, such as by hashing weighted voxel data (S900, S910) obtained from a machine vision system (110), and comparison of calculated signatures to cached data within a signature localization table (630) containing previously known voxel signatures and associated geospatial positions. Signature localization tables (630) may be developed by swarms of agents (1000) calculating signatures while traversing an environment and reporting calculated signatures and associated geospatial positions to a central server (1240). Once vehicles are localized, they may engage in semantic mapping. A swarm of vehicles (1400, 1402) may characterize assets encountered while traversing a local environment. Asset characterizations may be compared to known assets within the locally cached semantic map.
    Type: Grant
    Filed: September 29, 2018
    Date of Patent: November 26, 2019
    Assignee: SOLFICE RESEARCH, INC.
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Scott Harvey
  • Patent number: 10366289
    Abstract: Systems and methods for providing vehicle cognition through localization and semantic mapping are provided. Localization may involve in vehicle calculation of voxel signatures, such as by hashing weighted voxel data (S900, S910) obtained from a machine vision system (110), and comparison of calculated signatures to cached data within a signature localization table (630) containing previously known voxel signatures and associated geospatial positions. Signature localization tables (630) may be developed by swarms of agents (1000) calculating signatures while traversing an environment and reporting calculated signatures and associated geospatial positions to a central server (1240). Once vehicles are localized, they may engage in semantic mapping. A swarm of vehicles (1400, 1402) may characterize assets encountered while traversing a local environment. Asset characterizations may be compared to known assets within the locally cached semantic map.
    Type: Grant
    Filed: March 15, 2017
    Date of Patent: July 30, 2019
    Assignee: Solfice Research, Inc.
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Scott Harvey
  • Patent number: 10306689
    Abstract: Systems and methods allow for devices, such as sensory systems and mixed reality content consuming systems installed within a vehicle, to discover each other, share multidimensional realities, inherit context for mixed reality content, and/or coordinate whilst providing a mixed reality user experience. A discovery service can receive information from multiple devices and correlate digital and physical characteristics thereof to enable devices to discover each other. Characteristics of a device that may be used for pairing may include its orientation physically, the observable reality of a device, the state-machine of the device, the intentions of the device whilst operating autonomously or with external assistance, the location of a device, the temporal/spatial information describing the device's movement over time in a multi-dimensional reality or any unique identifiers contained within or generated by the device.
    Type: Grant
    Filed: February 9, 2018
    Date of Patent: May 28, 2019
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim
  • Publication number: 20190034730
    Abstract: Systems and methods for providing vehicle cognition through localization and semantic mapping are provided. Localization may involve in vehicle calculation of voxel signatures, such as by hashing weighted voxel data (S900, S910) obtained from a machine vision system (110), and comparison of calculated signatures to cached data within a signature localization table (630) containing previously known voxel signatures and associated geospatial positions. Signature localization tables (630) may be developed by swarms of agents (1000) calculating signatures while traversing an environment and reporting calculated signatures and associated geospatial positions to a central server (1240). Once vehicles are localized, they may engage in semantic mapping. A swarm of vehicles (1400, 1402) may characterize assets encountered while traversing a local environment. Asset characterizations may be compared to known assets within the locally cached semantic map.
    Type: Application
    Filed: September 29, 2018
    Publication date: January 31, 2019
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Scott Harvey
  • Publication number: 20190034728
    Abstract: Systems and methods for providing vehicle cognition through localization and semantic mapping are provided. Localization may involve in vehicle calculation of voxel signatures, such as by hashing weighted voxel data (S900, 5910) obtained from a machine vision system (110), and comparison of calculated signatures to cached data within a signature localization table (630) containing previously known voxel signatures and associated geospatial positions. Signature localization tables (630) may be developed by swarms of agents (1000) calculating signatures while traversing an environment and reporting calculated signatures and associated geospatial positions to a central server (1240). Once vehicles are localized, they may engage in semantic mapping. A swarm of vehicles (1400, 1402) may characterize assets encountered while traversing a local environment. Asset characterizations may be compared to known assets within the locally cached semantic map.
    Type: Application
    Filed: September 29, 2018
    Publication date: January 31, 2019
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Scott Harvey
  • Publication number: 20190034729
    Abstract: Systems and methods for providing vehicle cognition through localization and semantic mapping are provided. Localization may involve in vehicle calculation of voxel signatures, such as by hashing weighted voxel data (S900, S910) obtained from a machine vision system (110), and comparison of calculated signatures to cached data within a signature localization table (630) containing previously known voxel signatures and associated geospatial positions. Signature localization tables (630) may be developed by swarms of agents (1000) calculating signatures while traversing an environment and reporting calculated signatures and associated geospatial positions to a central server (1240). Once vehicles are localized, they may engage in semantic mapping. A swarm of vehicles (1400, 1402) may characterize assets encountered while traversing a local environment. Asset characterizations may be compared to known assets within the locally cached semantic map.
    Type: Application
    Filed: September 29, 2018
    Publication date: January 31, 2019
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Scott Harvey
  • Publication number: 20180370552
    Abstract: A system, method, and apparatus are disclosed for a machine vision system that incorporates hardware and/or software, remote databases, and algorithms to map assets, evaluate railroad track conditions, and accurately determine the position of a moving vehicle on a railroad track. One benefit of the invention is the possibility of real-time processing of sensor data for guiding operation of the moving vehicle.
    Type: Application
    Filed: August 29, 2018
    Publication date: December 27, 2018
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim
  • Patent number: 10086857
    Abstract: A system, method, and apparatus are disclosed for a machine vision system that incorporates hardware and/or software, remote databases, and algorithms to map assets, evaluate railroad track conditions, and accurately determine the position of a moving vehicle on a railroad track. One benefit of the invention is the possibility of real-time processing of sensor data for guiding operation of the moving vehicle.
    Type: Grant
    Filed: November 26, 2014
    Date of Patent: October 2, 2018
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim
  • Publication number: 20180227974
    Abstract: Systems and methods allow for devices, such as sensory systems and mixed reality content consuming systems installed within a vehicle, to discover each other, share multidimensional realities, inherit context for mixed reality content, and/or coordinate whilst providing a mixed reality user experience. A discovery service can receive information from multiple devices and correlate digital and physical characteristics thereof to enable devices to discover each other. Characteristics of a device that may be used for pairing may include its orientation physically, the observable reality of a device, the state-machine of the device, the intentions of the device whilst operating autonomously or with external assistance, the location of a device, the temporal/spatial information describing the device's movement over time in a multi-dimensional reality or any unique identifiers contained within or generated by the device.
    Type: Application
    Filed: February 9, 2018
    Publication date: August 9, 2018
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim
  • Publication number: 20180057030
    Abstract: Methods and apparatus for real time machine vision and point-cloud data analysis are provided, for remote sensing and vehicle control. Point cloud data can be analyzed via scalable, centralized, cloud computing systems for extraction of asset information and generation of semantic maps. Machine learning components can optimize data analysis mechanisms to improve asset and feature extraction from sensor data. Optimized data analysis mechanisms can be downloaded to vehicles for use in on-board systems analyzing vehicle sensor data. Semantic map data can be used locally in vehicles, along with onboard sensors, to derive precise vehicle localization and provide input to vehicle to control systems.
    Type: Application
    Filed: October 23, 2017
    Publication date: March 1, 2018
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Anuj Gupta, Scott Harvey, Jason Creadore, Graham Mills
  • Patent number: 9796400
    Abstract: Methods and apparatus for real time machine vision and point-cloud data analysis are provided, for remote sensing and vehicle control. Point cloud data can be analyzed via scalable, centralized, cloud computing systems for extraction of asset information and generation of semantic maps. Machine learning components can optimize data analysis mechanisms to improve asset and feature extraction from sensor data. Optimized data analysis mechanisms can be downloaded to vehicles for use in on-board systems analyzing vehicle sensor data. Semantic map data can be used locally in vehicles, along with onboard sensors, to derive precise vehicle localization and provide input to vehicle to control systems.
    Type: Grant
    Filed: January 20, 2016
    Date of Patent: October 24, 2017
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Anuj Gupta, Scott Harvey, Jason Creadore, Graham Mills
  • Publication number: 20170270361
    Abstract: Systems and methods for providing vehicle cognition through localization and semantic mapping are provided. Localization may involve in vehicle calculation of voxel signatures, such as by hashing weighted voxel data (S900, S910) obtained from a machine vision system (110), and comparison of calculated signatures to cached data within a signature localization table (630) containing previously known voxel signatures and associated geospatial positions. Signature localization tables (630) may be developed by swarms of agents (1000) calculating signatures while traversing an environment and reporting calculated signatures and associated geospatial positions to a central server (1240). Once vehicles are localized, they may engage in semantic mapping. A swarm of vehicles (1400, 1402) may characterize assets encountered while traversing a local environment. Asset characterizations may be compared to known assets within the locally cached semantic map.
    Type: Application
    Filed: March 15, 2017
    Publication date: September 21, 2017
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Scott Harvey
  • Publication number: 20160221592
    Abstract: Methods and apparatus for real time machine vision and point-cloud data analysis are provided, for remote sensing and vehicle control. Point cloud data can be analyzed via scalable, centralized, cloud computing systems for extraction of asset information and generation of semantic maps. Machine learning components can optimize data analysis mechanisms to improve asset and feature extraction from sensor data. Optimized data analysis mechanisms can be downloaded to vehicles for use in on-board systems analyzing vehicle sensor data. Semantic map data can be used locally in vehicles, along with onboard sensors, to derive precise vehicle localization and provide input to vehicle to control systems.
    Type: Application
    Filed: January 20, 2016
    Publication date: August 4, 2016
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim, Anuj Gupta, Scott Harvey, Jason Creadore, Graham Mills
  • Publication number: 20160121912
    Abstract: A system, method, and apparatus are disclosed for a machine vision system that incorporates hardware and/or software, remote databases, and algorithms to map assets, evaluate railroad track conditions, and accurately determine the position of a moving vehicle on a railroad track. One benefit of the invention is the possibility of real-time processing of sensor data for guiding operation of the moving vehicle.
    Type: Application
    Filed: November 26, 2014
    Publication date: May 5, 2016
    Applicant: SOLFICE RESEARCH, INC.
    Inventors: Shanmukha Sravan Puttagunta, Fabien Chraim