A system and method for intermodal container transport that utilizes swarm intelligence and the autonomous locating, lifting, supporting and moving via robots working in conjunction. A port central command locates and releases robots to the container location and then transports the container to its destination.

Mobile agents automatically manipulate components such as blocks on a working surface, to perform operations such as construction of generalized structures. The working surface and/or the components can have machine-readable codes to assist the agents in maintaining current knowledge of their respective locations. Agents identify components by type and location, and can move components according to directions; such directions can be provided by a user, or can be based on a pre-programmed directive, or can be determined dynamically based on current conditions or in response to actions of other agents. Agents may cooperate with one another. Agents can also respond to changes in the environment, alterations in works in progress, and/or other conditions, and may be configured to exhibit responses simulating emotional reactions. Different mobile agents can be associated with different character traits, which may be configured to change based on environmental conditions and/or the behavior of other mobile agents.

Disclosed are a tracking and identification method and system and an aircraft. The method includes: obtaining, by a first aircraft, a first feature parameter of a target object; if image data captured by the first aircraft does not match the first feature parameter, adjusting the first aircraft to a predetermined high-altitude area relative to the target object according to location information of a second aircraft that is sent by the second aircraft or location information of the target object, where the second aircraft is in a predetermined low-altitude area relative to the target object, and image data captured by the second aircraft matches a second feature parameter of the target object. The first aircraft in the predetermined high-altitude area and the second aircraft in the predetermined low-altitude area in embodiments of the present invention form high-low altitude cooperation and are respectively configured to track and identify the target object, thereby implementing transfer of location information between two or more aircrafts as well as tracking and identifying the target object.

Methods, systems, and apparatus, including computer programs encoded on computer storage media for evaluating robot learning. In some implementations, one or more computers receive object classification examples from a plurality of robots. Each object classification example includes (i) an embedding that a robot generated using a machine learning model, and (ii) an object classification corresponding to the embedding. The object classification examples are evaluated based on a similarity of the received embeddings with respect to other embeddings. A subset of the object classification examples is selected based on the evaluation of the quality of the embeddings. The subset of the object classification examples is distributed to the robots in the plurality of robots.

An apparatus for remotely controlling field robots, includes: an interface unit; a work command generator generating a work command signal for operating field robots; an autonomous command generator which generates an autonomous operation command signal for controlling an operation of a second field robot when a user selects a following mode and the work command generator generates a work command signal for a first field robot to correspond to the following mode, or generates an autonomous operation command signal for controlling operations of the first field robot and the second field robot in order to operate an object of work when the user selects an object mode and the work command generator generates a work command signal for the object of work to correspond to the object mode; and a communication unit transmitting the generated autonomous operation command signal to the first field robot and the second field robots.

A robot system includes a robot including a robot main body having a receiving unit that receives a predetermined operation, a control apparatus that controls actuation of the robot main body, and a transmitting unit that, when the receiving unit receives the operation, transmits information representing reception of the operation, and an instruction apparatus having a receiving unit that receives the information transmitted by the transmitting unit and a first reporting unit, and instructing the control apparatus to execute an operation program, wherein, when the instruction apparatus is in a condition with a right for control in which the instruction apparatus can instruct the control apparatus to execute the operation program, when the receiving unit receives the information, the first reporting unit reports that the instruction apparatus is in the condition with the right for control.

Industrial robotic platforms are described. The robotic platform includes a universal platform configured to attach to interchangeable task-specific tooling systems and mobility systems. The robots may be mining robots, with a mining-specific tooling system attached to the universal platform, 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. The robot may be included in a swarm or colony as part of an overall autonomous architecture. The robot may be part of an architecture having a colony or remote control center that communicates with and monitors the robots.

A sensing system includes a sensor with a computing system and a memory in communication with the computing system, the memory storing a plurality of endpoints. The computing system is configured to receive activity preferences from a device at an endpoint and further determines the likeability of the activities at the endpoint. Further, it receives semantic identification preferences from the device in communication with the computing system and the system blurs the corresponding semantic identities based on the received preferences.

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.

A modular robot system is capable of being configured to allow a plurality of cube-shaped unit robots to be coupled to one another. The modular robot system has N cube-shaped unit robots (where N is an integer greater than 2), each cube-shaped unit robot including: a cube-shaped housing; a step motor located inside the housing; and a controller located inside the housing to control the step motor, wherein the housing has a mounting groove formed on one surface thereof to mount a rotary body rotating by a rotary shaft of the step motor thereon and connection grooves with the same shape as each other formed on the five surfaces thereof, so that through connectors mounted on the connection grooves, one cube-shaped unit robot is connectable to another cube-shaped unit robot.