Method and System for Feedback Data Collection

A method for collecting data for fine-tuning a machine learning model to control a robotic device, the method comprising the steps of:

• a) receiving a request for initiating an action to be performed by a robotic device;
• b) processing the request to identify a machine learning model associated with the requested action;
• c) providing access to the machine learning model to a controller of one or both of the robotic device a teleoperation device and instructing the controller of the relevant device to execute the model, wherein the teleoperation device includes a morphology matching kinematic chain structure corresponding to a kinematic chain structure of the robotic device, wherein each joint and link of the robotic device has a corresponding joint and link on the teleoperation device;
• d) receiving feedback data from at least one of the controllers, the feedback data including data relating to a human-based input provided via the teleoperation device;
• and
• e) processing the feedback data to update the machine learning model, wherein processing the feedback data includes:
• (i) aggregating a training dataset associated with the machine learning model with the feedback data;
• and
• (ii) re-training the machine learning model using the aggregated training dataset.

A system for collecting data for fine-tuning a machine learning model to control a robotic device, the system comprising:

• a) a memory for storing computer-readable program code and a processor for executing the computer-readable program code;
• b) a request receiving component configured to receive a request for initiating an action to be performed by a robotic device;
• c) a request processing component configured to process the request to identify a machine learning model associated with the requested action;
• d) a machine learning component configured to provide access to the machine learning model to a controller of one or both of the robotic device and a teleoperation device and instructing the controller to execute the model;
• e) a feedback receiving component configured to receive feedback data from at least one of the controllers, the feedback data including data relating to a human-based input provided via the teleoperation device;
• and
• f) a feedback processing component configured to process the feedback data to update the machine learning model, wherein processing the feedback data includes aggregating a training dataset associated with the machine learning model with the feedback data and re-training the machine learning model using the aggregated training dataset.