Systems and methods for distributed training and management of AI-powered robots using teleoperation via virtual spaces

At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform:

• receiving, from one or more sensors, sensor data relating to a robot, wherein the sensor data comprises a voxel grid relating to the robot, wherein each voxel in the voxel grid is either occupied or not occupied, wherein the voxel grid is generated by capturing a three-dimensional point cloud relating to the robot, segmenting the three-dimensional point cloud into one or more object point clouds, and converting the one or more object point clouds into the voxel grid;
• generating, using a statistical model, based on the sensor data, first control information for the robot to accomplish a task;
• transmitting, to the robot, the first control information for execution of the task;
• and
• receiving, from the robot, a result of execution of the task.

A method, comprising:

• receiving, from one or more sensors, sensor data relating to a robot, wherein the sensor data comprises a voxel grid relating to the robot, wherein each voxel in the voxel grid is either occupied or not occupied, wherein the voxel grid is generated by capturing a three-dimensional point cloud relating to the robot, segmenting the three-dimensional point cloud into one or more object point clouds, and converting the one or more object point clouds into the voxel grid;
• generating, using a statistical model, based on the sensor data, first control information for the robot to accomplish a task;
• transmitting, to the robot, the first control information for execution of the task;
• and
• receiving, from the robot, a result of execution of the task.