Patents by Inventor Anjali Krishnamachar

Anjali Krishnamachar 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: 20220207387
    Abstract: Systems and methods are provided for predicting drawbridge operation based on incoming vessel information and historical drawbridge operation data, and transmitting the drawbridge operation prediction to a GPS system such as an autonomous vehicle or a mobile device application for rerouting a planned navigation route. A transceiver may receive vessel information, e.g., incoming vessel size, type, speed, position, or quantity, or estimated incoming vessel arrival time, from one or more cameras and/or a marine radio, and may receive historical drawbridge operation data based on the incoming vessel information from an online database such that the drawbridge operation prediction is based on the historical data.
    Type: Application
    Filed: December 28, 2020
    Publication date: June 30, 2022
    Applicant: Ford Global Technologies, LLC
    Inventors: Anjali Krishnamachar, Matthew A. Warner, Umair Ibrahim
  • Patent number: 10726248
    Abstract: The present invention extends to methods, systems, and computer program products for validating gesture recognition capabilities of automated systems. Aspects include a gesture recognition training system that is scalable, efficient, repeatable, and accounts for permutations of physical characteristics, clothing, types of gestures, environment, culture, weather, road conditions, etc. The gesture recognition training system includes sensors and algorithms used to generate training data sets that facilitate more accurate recognition of and reaction to human gestures. A training data set can be scaled from both monitoring and recording gestures performed by a humanoid robot and performed by animated humans in a simulation environment. From a scaled training data set, autonomous devices can be trained to recognize and react to a diverse set of human gestures in varying conditions with substantially improved capabilities.
    Type: Grant
    Filed: February 1, 2018
    Date of Patent: July 28, 2020
    Assignee: FORD GLOBAL TECHNOLOGIES, LLC
    Inventors: Venkatapathi Raju Nallapa, Anjali Krishnamachar, Gautham Sholingar
  • Publication number: 20200079165
    Abstract: A hitch assist system is provided herein. The hitch assist system includes a sensing system having an imager and a proximity sensor. The hitch assist system also includes a controller for receiving signals from the proximity sensor and generating a feature map; determining a coupler location based on the detected features; and maneuvering the vehicle along a path to align a hitch ball with a coupler of the trailer.
    Type: Application
    Filed: September 10, 2018
    Publication date: March 12, 2020
    Inventors: Luke Niewiadomski, Bruno Sielly Jales Costa, Anjali Krishnamachar, Douglas Rogan
  • Publication number: 20190236341
    Abstract: The present invention extends to methods, systems, and computer program products for validating gesture recognition capabilities of automated systems. Aspects include a gesture recognition training system that is scalable, efficient, repeatable, and accounts for permutations of physical characteristics, clothing, types of gestures, environment, culture, weather, road conditions, etc. The gesture recognition training system includes sensors and algorithms used to generate training data sets that facilitate more accurate recognition of and reaction to human gestures. A training data set can be scaled from both monitoring and recording gestures performed by a humanoid robot and performed by animated humans in a simulation environment. From a scaled training data set, autonomous devices can be trained to recognize and react to a diverse set of human gestures in varying conditions with substantially improved capabilities.
    Type: Application
    Filed: February 1, 2018
    Publication date: August 1, 2019
    Inventors: Venkatapathi Raju Nallapa, Anjali Krishnamachar, Gautham Sholingar