Dynamic vision system for robot fleet management

A dynamic vision system for robot fleet management, comprising:

• an optical assembly including a lens containing a liquid, wherein the lens is deformable to generate variable focus for the lens, and wherein the optical assembly is configured to capture optical data;
• a robot fleet management platform having a control system configured to adjust one or more optical parameters, wherein the one or more optical parameters modify the variable focus of the lens while the optical assembly captures current optical data relating to a robotic fleet, and wherein the robot fleet management platform pauses robotic activity of at least one robotic apparatus upon detection of a numeric score not meeting or exceeding a stored numeric score threshold;
• and
• a processing system configured to train a machine learning model to recognize an object relating to the robotic fleet using training data generated from the optical data captured by the optical assembly, wherein the optical data includes the current optical data relating to the robotic fleet.

A computer-implemented method for robot fleet management, comprising:

• capturing optical data using an optical assembly including a lens containing a liquid, wherein the lens is deformable to generate variable focus for the lens;
• adjusting one or more optical parameters to modify the variable focus of the lens while the optical assembly captures current optical data relating to a robotic fleet;
• generating training data from the optical data captured by the optical assembly, wherein the optical data includes the current optical data relating to the robotic fleet, and wherein the optical data captured by the optical assembly includes optical data that is out-of-focus with respect to an object being optically captured by the optical assembly;
• and
• training a machine learning model to recognize an object relating to the robotic fleet using the training data.

A computer-implemented method for robot fleet management, comprising:

• capturing optical data using an optical assembly including a lens containing a liquid, wherein the lens is deformable to generate variable focus for the lens;
• adjusting one or more optical parameters to modify the variable focus of the lens while the optical assembly captures current optical data relating to a robotic fleet;
• generating training data from the optical data captured by the optical assembly, wherein the optical data includes the current optical data relating to the robotic fleet;
• training a machine learning model to recognize an object relating to the robotic fleet using the training data;
• and
• pausing robotic activity of at least one robotic apparatus upon detection of a numeric score not meeting or exceeding a stored numeric score threshold.