Real-time multi-robot collaboration in dynamic environments

A computer-implemented method for performing real-time multi-robot collaboration in dynamic environments, the computer-implemented method comprising:

• obtaining, by one or more processors from sensors of a robot of a robot fleet, sensor data of an environment of the robot, wherein the robot fleet is configured to perform a mission in the environment that is unknown to the robot fleet;
• generating, via the one or more processors, tokenized sensor data by tokenizing the sensor data;
• inputting, by the one or more processors, the tokenized sensor data into a robotics foundational model (RFM) associated with the robot causing the RFM to generate insight data used for making decisions associated with performing the mission, wherein generating the insight data includes:
• generating, by the one or more processors via a belief model based upon the tokenized sensor data, belief data indicating one or more beliefs about the environment, wherein the belief data indicates a portion of the environment associated with a belief and a confidence metric associated with the belief;
• and
• generating, by the one or more processors, one or more risk-reward maps, each risk-reward map indicating one or more of a potential risk or a potential reward associated with the robot performing the mission, wherein the insight data includes the belief data and the one or more risk-reward maps;
• and
• implementing a token sharing policy causing the robot to perform:
• generating, by the one or more processors, tokenized insight data by tokenizing the insight data;
• and
• transmitting, by the one or more processors, the tokenized insight data to one or more recipient robots of the robot fleet.

A non-transitory computer-readable medium storing processor-executable instructions that, when executed by one or more processors, cause the one or more processors to:

• obtain, from sensors of a robot of a robot fleet, sensor data of an environment of the robot, wherein the robot fleet is configured to perform a mission in the environment that is unknown to the robot fleet;
• generate tokenized sensor data by tokenizing the sensor data;
• input the tokenized sensor data into a robotics foundational model (RFM) associated with the robot causing the RFM to generate insight data used for making decisions associated with performing the mission, wherein generating the insight data includes:
• generating, via a belief model based upon the tokenized sensor data, belief data indicating one or more beliefs about the environment, wherein the belief data indicates a portion of the environment associated with a belief and a confidence metric associated with the belief;
• and
• generating one or more risk-reward maps, each risk-reward map indicating one or more of a potential risk or a potential reward associated with the robot performing the mission, wherein the insight data includes the belief data and the one or more risk-reward maps;
• and
• implement a token sharing policy causing the robot to perform:
• generating tokenized insight data by tokenizing the insight data;
• and
• transmitting the tokenized insight data to one or more recipient robots of the robot fleet.