Patents by Inventor Samir Parikh

Samir Parikh 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: 20250162616
    Abstract: A machine-learned architecture may predict a set of spatially-diverse paths that an object may take in the future. The paths generated by this architecture may be time-invariant (e.g., not identifying a time at which the object may occupy a position along one of these paths) but can be used by a second machine-learned model to predict progress in time along these paths. This segregation of the spatial paths and progress in time along the paths improves the accuracy of the ultimate prediction and better captures rare object behavior.
    Type: Application
    Filed: November 21, 2023
    Publication date: May 22, 2025
    Inventors: Gregory Michael Woelki, Xiaosi Zeng, Gowtham Garimella, Samir Parikh, Ethan Miller Pronovost
  • Patent number: 12296858
    Abstract: Techniques for determining a response of a simulated vehicle to a simulated object in a simulation are discussed herein. Log data captured by a physical vehicle in an environment can be received. Object data representing an object in the log data can be used to instantiate a simulated object in a simulation to determine a response of a simulated vehicle to the simulated object. Additionally, one or more trajectory segments in a trajectory library representing the log data can be determined and instantiated as a trajectory of the simulated object in order to increase the accuracy and realism of the simulation.
    Type: Grant
    Filed: November 18, 2021
    Date of Patent: May 13, 2025
    Assignee: Zoox, Inc.
    Inventors: Andres Guillermo Morales Morales, Samir Parikh, Kai Zhenyu Wang
  • Patent number: 12291240
    Abstract: Techniques for determining a response of a simulated vehicle to a simulated object in a simulation are discussed herein. Log data captured by a physical vehicle in an environment can be received. Object data representing an object in the log data can be used to instantiate a simulated object in a simulation to determine a response of a simulated vehicle to the simulated object. Additionally, one or more trajectory segments in a trajectory library representing the log data can be determined and instantiated as a trajectory of the simulated object in order to increase the accuracy and realism of the simulation.
    Type: Grant
    Filed: November 18, 2021
    Date of Patent: May 6, 2025
    Assignee: Zoox, Inc.
    Inventors: Andres Guillermo Morales Morales, Samir Parikh, Kai Zhenyu Wang
  • Patent number: 11847831
    Abstract: Techniques for determining a classification probability of an object in an environment are discussed herein. Techniques may include analyzing sensor data associated with an environment from a perspective, such as a top-down perspective, using multi-channel data. From this perspective, techniques may determine channels of multi-channel input data and additional feature data. Channels corresponding to spatial features may be included in the multi-channel input data and data corresponding to non-spatial features may be included in the additional feature data. The multi-channel input data may be input to a first portion of a machine-learned (ML) model, and the additional feature data may be concatenated with intermediate output data from the first portion of the ML model, and input into a second portion of the ML model for subsequent processing and to determine the classification probabilities. Additionally, techniques may be performed on a multi-resolution voxel space representing the environment.
    Type: Grant
    Filed: December 30, 2020
    Date of Patent: December 19, 2023
    Assignee: Zoox, Inc.
    Inventor: Samir Parikh
  • Patent number: 11829449
    Abstract: Techniques for determining a classification probability of an object in an environment are discussed herein. Techniques may include analyzing sensor data associated with an environment from a perspective, such as a top-down perspective, using multi-channel data. From this perspective, techniques may determine channels of multi-channel input data and additional feature data. Channels corresponding to spatial features may be included in the multi-channel input data and data corresponding to non-spatial features may be included in the additional feature data. The multi-channel input data may be input to a first portion of a machine-learned (ML) model, and the additional feature data may be concatenated with intermediate output data from the first portion of the ML model, and input into a second portion of the ML model for subsequent processing and to determine the classification probabilities. Additionally, techniques may be performed on a multi-resolution voxel space representing the environment.
    Type: Grant
    Filed: December 30, 2020
    Date of Patent: November 28, 2023
    Assignee: Zoox, Inc.
    Inventor: Samir Parikh
  • Patent number: 11708093
    Abstract: Techniques to predict object behavior in an environment are discussed herein. For example, such techniques may include determining a trajectory of the object, determining an intent of the trajectory, and sending the trajectory and the intent to a vehicle computing system to control an autonomous vehicle. The vehicle computing system may implement a machine learned model to process data such as sensor data and map data. The machine learned model can associate different intentions of an object in an environment with different trajectories. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on object's intentions and trajectories.
    Type: Grant
    Filed: May 8, 2020
    Date of Patent: July 25, 2023
    Assignee: Zoox, Inc.
    Inventors: Kenneth Michael Siebert, Gowtham Garimella, Benjamin Isaac Mattinson, Samir Parikh, Kai Zhenyu Wang
  • Publication number: 20230150549
    Abstract: Techniques for determining a response of a simulated vehicle to a simulated object in a simulation are discussed herein. Log data captured by a physical vehicle in an environment can be received. Object data representing an object in the log data can be used to instantiate a simulated object in a simulation to determine a response of a simulated vehicle to the simulated object. Additionally, one or more trajectory segments in a trajectory library representing the log data can be determined and instantiated as a trajectory of the simulated object in order to increase the accuracy and realism of the simulation.
    Type: Application
    Filed: November 18, 2021
    Publication date: May 18, 2023
    Inventors: Andres Guillermo Morales Morales, Samir Parikh, Kai Zhenyu Wang
  • Patent number: 11554790
    Abstract: Techniques to predict object behavior in an environment are discussed herein. For example, such techniques may include inputting data into a model and receiving an output from the model representing a discretized representation. The discretized representation may be associated with a probability of an object reaching a location in the environment at a future time. A vehicle computing system may determine a trajectory and a weight associated with the trajectory using the discretized representation and the probability. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on the trajectory and the weight output by the vehicle computing system.
    Type: Grant
    Filed: May 8, 2020
    Date of Patent: January 17, 2023
    Assignee: Zoox, Inc.
    Inventors: Kenneth Michael Siebert, Gowtham Garimella, Samir Parikh
  • Publication number: 20220207308
    Abstract: Techniques for determining a classification probability of an object in an environment are discussed herein. Techniques may include analyzing sensor data associated with an environment from a perspective, such as a top-down perspective, using multi-channel data. From this perspective, techniques may determine channels of multi-channel input data and additional feature data. Channels corresponding to spatial features may be included in the multi-channel input data and data corresponding to non-spatial features may be included in the additional feature data. The multi-channel input data may be input to a first portion of a machine-learned (ML) model, and the additional feature data may be concatenated with intermediate output data from the first portion of the ML model, and input into a second portion of the ML model for subsequent processing and to determine the classification probabilities. Additionally, techniques may be performed on a multi-resolution voxel space representing the environment.
    Type: Application
    Filed: December 30, 2020
    Publication date: June 30, 2022
    Inventor: Samir Parikh
  • Publication number: 20220207275
    Abstract: Techniques for determining a classification probability of an object in an environment are discussed herein. Techniques may include analyzing sensor data associated with an environment from a perspective, such as a top-down perspective, using multi-channel data. From this perspective, techniques may determine channels of multi-channel input data and additional feature data. Channels corresponding to spatial features may be included in the multi-channel input data and data corresponding to non-spatial features may be included in the additional feature data. The multi-channel input data may be input to a first portion of a machine-learned (ML) model, and the additional feature data may be concatenated with intermediate output data from the first portion of the ML model, and input into a second portion of the ML model for subsequent processing and to determine the classification probabilities. Additionally, techniques may be performed on a multi-resolution voxel space representing the environment.
    Type: Application
    Filed: December 30, 2020
    Publication date: June 30, 2022
    Inventor: Samir Parikh
  • Publication number: 20220164951
    Abstract: Examples of the present disclosure describe systems and methods for using AI to identify regions of interest (ROI) in medical images. In aspects, medical reports and images may be provided to a first environment. The first environment may use the medical report data/medical images to train a natural language processing (NLP)-based algorithm to identify the location in images of ROI described in the medical report data. The output of the NLP-based algorithm may be stored in an ROI repository in the first environment. After the NLP-based algorithm has been trained, a request to train a user-specific model may be received in a second environment. Data objects for the requested user-specific model may be provided to the first environment, which uses the ROI repository to train the model. The trained model may be provided to the second environment, where the trained user-specific model/algorithm may be tested and stored.
    Type: Application
    Filed: November 19, 2021
    Publication date: May 26, 2022
    Applicant: Hologic, Inc.
    Inventors: Haili Chui, Nikolaos Gkanatsios, Zhenxue Jing, Ashwini Kshirsagar, Samir Parikh, Venky Vaddineni
  • Publication number: 20220164586
    Abstract: Examples of the present disclosure describe systems and methods for using AI to identify regions of interest (ROI) in medical images. In aspects, medical reports and images may be provided to a second environment. The second environment may use the medical report data/medical images to train a natural language processing (NLP)-based algorithm to identify the location in images of ROI described in the medical report data. The output of the NLP-based algorithm may be stored in an ROI repository in the second environment. After the NLP-based algorithm has been trained, a request to train a user-specific model may be received in a first environment. Data objects for the requested user-specific model may be provided to the second environment, which uses the ROI repository to train the model. The trained model may be provided to the first environment, where the trained user-specific model/algorithm may be tested and stored.
    Type: Application
    Filed: November 22, 2021
    Publication date: May 26, 2022
    Applicant: Hologic, Inc.
    Inventors: Haili Chui, Nikolaos Gkanatsios, Zhenxue Jing, Ashwini Kshirsagar, Samir Parikh, Venky Vaddineni
  • Publication number: 20210347377
    Abstract: Techniques to predict object behavior in an environment are discussed herein. For example, such techniques may include inputting data into a model and receiving an output from the model representing a discretized representation. The discretized representation may be associated with a probability of an object reaching a location in the environment at a future time. A vehicle computing system may determine a trajectory and a weight associated with the trajectory using the discretized representation and the probability. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on the trajectory and the weight output by the vehicle computing system.
    Type: Application
    Filed: May 8, 2020
    Publication date: November 11, 2021
    Inventors: Kenneth Michael Siebert, Gowtham Garimella, Samir Parikh
  • Publication number: 20210347383
    Abstract: Techniques to predict object behavior in an environment are discussed herein. For example, such techniques may include determining a trajectory of the object, determining an intent of the trajectory, and sending the trajectory and the intent to a vehicle computing system to control an autonomous vehicle. The vehicle computing system may implement a machine learned model to process data such as sensor data and map data. The machine learned model can associate different intentions of an object in an environment with different trajectories. A vehicle, such as an autonomous vehicle, can be controlled to traverse an environment based on object's intentions and trajectories.
    Type: Application
    Filed: May 8, 2020
    Publication date: November 11, 2021
    Inventors: Kenneth Michael Siebert, Gowtham Garimella, Benjamin Isaac Mattinson, Samir Parikh, Kai Zhenyu Wang
  • Patent number: 11014231
    Abstract: A method may include obtaining a task-specific state of a robotic device associated with performing a task by the robotic device. The method may also include mapping the task-specific state to a general state of the robotic device, where the general state may applicable to multiple tasks and may include a variable number of elements. The method may additionally include obtaining a set of generic actions represented by a set of parameters, where the set of generic actions may be used to perform the multiple tasks. The method may also include processing the general state of the robotic device to solve for the set of parameters and to predict a next action in performing the task, where the next action may be selected from the set of generic actions, and performing the next action using the set of parameters solved for.
    Type: Grant
    Filed: May 3, 2018
    Date of Patent: May 25, 2021
    Assignee: FUJITSU LIMITED
    Inventors: Samir Parikh, Wing-Yue Geoffrey Louie
  • Patent number: 10997258
    Abstract: A bot network system may be provided. A system may include a plurality of bot agents, wherein at least one bot agent of the plurality of bot agents is configured to receive a request from a user in natural language. The system may further include a plurality of digital resources including one or more of a software program, a service, a web service and a dataset. Each digital resource of the plurality of digital resources may be configured to communicate with a dedicated bot agent of the plurality of bot agents. Also, each bot agent may be configured to interact with its associated digital resource via an application programming interface (API) of the associated digital resource and translate between the natural language and a language of the associated digital resource.
    Type: Grant
    Filed: February 28, 2018
    Date of Patent: May 4, 2021
    Assignee: FUJITSU LIMITED
    Inventors: Wei-Peng Chen, Lei Liu, Mehdi Bahrami, Samir Parikh, Junhee Park
  • Publication number: 20190337150
    Abstract: A method may include obtaining a task-specific state of a robotic device associated with performing a task by the robotic device. The method may also include mapping the task-specific state to a general state of the robotic device, where the general state may applicable to multiple tasks and may include a variable number of elements. The method may additionally include obtaining a set of generic actions represented by a set of parameters, where the set of generic actions may be used to perform the multiple tasks. The method may also include processing the general state of the robotic device to solve for the set of parameters and to predict a next action in performing the task, where the next action may be selected from the set of generic actions, and performing the next action using the set of parameters solved for.
    Type: Application
    Filed: May 3, 2018
    Publication date: November 7, 2019
    Applicant: FUJITSU LIMITED
    Inventors: Samir PARIKH, Wing-Yue Geoffrey LOUIE
  • Publication number: 20190266287
    Abstract: A bot network system may be provided. A system may include a plurality of bot agents, wherein at least one bot agent of the plurality of bot agents is configured to receive a request from a user in natural language. The system may further include a plurality of digital resources including one or more of a software program, a service, a web service and a dataset. Each digital resource of the plurality of digital resources may be configured to communicate with a dedicated bot agent of the plurality of bot agents. Also, each bot agent may be configured to interact with its associated digital resource via an application programming interface (API) of the associated digital resource and translate between the natural language and a language of the associated digital resource.
    Type: Application
    Filed: February 28, 2018
    Publication date: August 29, 2019
    Applicant: FUJITSU LIMITED
    Inventors: Wei-Peng CHEN, Lei LIU, Mehdi BAHRAMI, Samir PARIKH, Junhee PARK
  • Patent number: 9977965
    Abstract: A method may include obtaining first images, each image including an object, and determining a set of one or more visual cues for each. The method may include selecting a common visual cue of the one or more visual cues that is common to each set of one or more visual cues determined for each corresponding image and determining a correlation between a location of the common visual cue in each image of the first images and a location of the object in each image of the first images. The method may include obtaining a second image of an environment and identifying the common visual cue in the second image. The method may include determining a placement location for the object in the environment based on the correlation and a location of the common visual cue in the second image.
    Type: Grant
    Filed: June 26, 2017
    Date of Patent: May 22, 2018
    Assignee: FUJITSU LIMITED
    Inventor: Samir Parikh
  • Patent number: D827451
    Type: Grant
    Filed: September 14, 2016
    Date of Patent: September 4, 2018
    Assignee: Polarpak, Inc.
    Inventors: Samir Parikh, Jaskaran Sukhija