Enhancing robot learning
AssigneeX Development LLC
InventorsNareshkumar Rajkumar, Patrick Leger, Abhinav Gupta
Life of this patent
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Abstract
Methods, systems, and apparatus, including computer-readable media storing executable instructions, for enhancing robot learning. In some implementations, a robot stores first embeddings generated using a first machine learning model, and the first embeddings include one or more first private embeddings that are not shared with other robots. The robot receives a second machine learning model from a server system over a communication network. The robot generates a second private embedding for each of the one or more first private embeddings using the second machine learning model. The robot adds the second private embeddings to the cache of the robot and removes the one or more first private embeddings from the cache of the robot.
Claims20
A method comprising:
- storing, by a robot, first embeddings generated using a first machine learning model, wherein the robot stores the first embeddings in a cache of the robot, wherein the first embeddings include one or more first private embeddings that are not shared with other robots;
- receiving, by the robot, a second machine learning model from a server system over a communication network;
- generating, by the robot, a second private embedding for each of the one or more first private embeddings in the cache, wherein each of the second private embeddings is generated using the second machine learning model;
- adding, by the robot, the second private embeddings to the cache of the robot;
- and
- removing, by the robot, the one or more first private embeddings from the cache of the robot.
A robot comprising:
- one or more processors;
- and
- one or more machine-readable storage devices storing instructions that, when executed by the one or more processors, cause the robot to perform operations comprising:
- storing, by the robot, first embeddings generated using a first machine learning model, wherein the robot stores the first embeddings in a cache of the robot, wherein the first embeddings include one or more first private embeddings that are not shared with other robots;
- receiving, by the robot, a second machine learning model from a server system over a communication network;
- generating, by the robot, a second private embedding for each of the one or more first private embeddings in the cache, wherein each of the second private embeddings is generated using the second machine learning model;
- adding, by the robot, the second private embeddings to the cache of the robot;
- and
- removing, by the robot, the one or more first private embeddings from the cache of the robot.
One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors, cause a robot to perform operations comprising:
- storing, by the robot, first embeddings generated using a first machine learning model, wherein the robot stores the first embeddings in a cache of the robot, wherein the first embeddings include one or more first private embeddings that are not shared with other robots;
- receiving, by the robot, a second machine learning model from a server system over a communication network;
- generating, by the robot, a second private embedding for each of the one or more first private embeddings in the cache, wherein each of the second private embeddings is generated using the second machine learning model;
- adding, by the robot, the second private embeddings to the cache of the robot;
- and
- removing, by the robot, the one or more first private embeddings from the cache of the robot.
Dependencies are inferred from the claim text.