Deep Context Maps

Systems and methods for predicting the trajectory of an object are disclosed herein. One embodiment receives sensor data that includes a location of the object in an environment of the object; accesses a location-specific latent map, the location-specific latent map having been learned together with a neural-network-based trajectory predictor during a training phase, wherein the neural-network-based trajectory predictor is deployed in a robot; inputs, to the neural-network-based trajectory predictor, the location of the object and the location-specific latent map, the location-specific latent map providing, to the neural-network-based trajectory predictor, a set of location-specific biases regarding the environment of the object; and outputs, from the neural-network-based trajectory predictor, a predicted trajectory of the object.

Researchers

Daniela Rus / Guy Rosman / Sertac Karaman / Igor Gilitschenski / Arjun Gupta

Departments: Dept of Electrical Engineering & Computer Science, Department of Aeronautics and Astronautics
Technology Areas: Artificial Intelligence (AI) and Machine Learning (ML) / Computer Science: Bioinformatics / Sensing & Imaging: Optical Sensing

  • systems and methods for predicting the trajectory of an object with the aid of a location-specific latent map
    United States of America | Granted | 11,427,210

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