A method of robotic collaboration comprises designating a first robot a lead robot and assigning a first task in a task area to the lead robot. Broadcasting a work query in the task area seeks the presence of subordinate robots configured to perform tasks. Receiving a work confirmation signal from a subordinate robot in the task area answers the work query with an affirmation that the subordinate robot is in the task area to perform tasks. Transmitting a task command to the subordinate robot in response to the work confirmation signal comprises a directive to perform the first task. Receiving a task confirmation signal informs the lead robot of the subordinate robot electronic characteristics comprising processing capabilities, transmit signal profile, receive signal profile, and storage device capabilities. Processing confirms whether the subordinate robot can collaborate with the lead robot to do the first task.

A method of controlling at least one of a first robot and a second robot to collaborate within a system, the first robot and the second robot being physically separate to one another, the method including: receiving sensed data associated with the second robot; determining position and/or orientation of the second robot using the received sensed data; determining an action for the second robot using the determined position and/or orientation of the second robot; and providing a control signal to the second robot to cause the second robot to perform the determined action to collaborate with the first robot.

Systems and methods for industrial robotic platforms. Squads of industrial robots autonomously communicate and work together. A control center may monitor the autonomous operations. Software at the control center, squad, and robot levels forms a distributed control system that analyzes various data related to the platform for monitoring of the various systems. Artificial intelligence, such as machine learning, is implemented at the control center, squad, and/or robot levels for swarm behavior driven by intelligent decision making. Each robot includes a universal platform attached to a task-specific tooling system. The robots may be mining robots, with a mining-specific tooling system attached to the universal framework, and configured for mining tasks. The platform is modular and may be used for other industrial applications and/or robot types, such as construction, satellite swarms, fuel production, disaster recovery, communications, remote power, and others.

Methods and systems for allocating tasks to robotic devices are provided. An example method includes receiving information associated with task logs for a plurality of robotic devices and in a computing system configured to access a processor and memory, determining information associated with a health level for the plurality of robotic devices based on the information associated with the task logs. A health level for a given robotic device may be proportional to a current level of ability to perform a function, which may change over a lifespan of the given robotic device. Information associated with a plurality of tasks to be performed by one or more or the robotic devices may also be determined. The computing system may optimize an allocation of the plurality of tasks such that a high precision task may be allocated to a robotic device having a greater current health level than another robotic device.

A method of robotic collaboration comprises designating a first robot a lead robot and assigning a first task in a task area to the lead robot. Broadcasting a work query in the task area seeks the presence of subordinate robots configured to perform tasks. Receiving a work confirmation signal from a subordinate robot in the task area answers the work query with an affirmation that the subordinate robot is in the task area to perform tasks. Transmitting a task command to the subordinate robot in response to the work confirmation signal comprises a directive to perform the first task. Receiving a task confirmation signal informs the lead robot of the subordinate robot electronic characteristics comprising processing capabilities, transmit signal profile, receive signal profile, and storage device capabilities. Processing confirms whether the subordinate robot can collaborate with the lead robot to do the first task.

A method for operating a multi-agent system that includes multiple robots, each of the robots cyclically performing the following: starting from an instantaneous system state, ascertaining possible options, the options defining actions by which a transition may be achieved from an instantaneous system state to a subsequent system state; for each of the possible options, ascertaining action costs for performing an action specified by the option; performing an auction, the action costs values ascertained for each option being taken into consideration by each of the other robots; and performing an action, which corresponds to one of the options, as a function of all cost values ascertained or received for the relevant option, the action costs for a particular option each taking an experience parameter into consideration, which is a function of costs for past actions assigned to the particular option previously carried out by the multiple robots.

An exemplary multi-robot system can include, for example, a first robot(s), which can include a communication arrangement and a sensor arrangement configured to detect a presence of an object(s) within a predetermined distance from the first robot(s), and determine a distance from the first robot(s) to the object(s), where the first robot(s) can broadcast a query to the object(s) using the communication arrangement, identify the object(s) as a second robot(s) or a non-robot based on a response received from the object(s). The sensor arrangement can be a Light Detection and Ranging (LiDAR) sensor arrangement. The LiDAR sensor arrangement can be a two-dimensional LiDAR sensor arrangement.

Embodiments of the present invention provide a method, system and computer program product for teaming in swarm intelligent robot sets. The method includes programming a multiplicity of robots in a multi-robot set with a particular locomotive model and assigning each of the robots to different individual tasks corresponding to different individual objectives of a problem based upon the particular locomotive model of the corresponding robots. The method additionally includes deploying the multi-robot set into a confined geographic area and surveilling each robot to ensure that each robot assigned to a corresponding task is achieving the assigned task. Finally, the method includes responding to one of the robots appearing to be unable to complete a corresponding assigned one of the tasks by selecting a different robot with a locomotive model considered compatible with the corresponding assigned one of the tasks to complete the corresponding assigned one of the tasks.

A near real-time custom server system includes robots deployed at a data center location and a server assembly controller configured to receive requests for near-real time custom servers. The requests may specify one or more characteristics for the custom servers and the server assembly controller may cause the robots deployed at the data center location to assemble the custom servers and install the custom servers in a server mounting structure of the data center in near real-time. For custom server types requested in lower volumes, the custom servers may be assembled autonomously by respective ones of the robots; and for custom server types requested in higher volumes, the custom servers may be assembled by respective groups of robots working in coordination with one another via an assembly line.

A system for localizing a swarm of robotic platforms utilizing ranging sensors. The swarm is localized by purposely leaving some of the platforms of the swarm stationary, providing localization to the moving ones. The platforms in the swarm can alternate between a stationary and moving state.