A robotic cart includes a bin, at least one mobile device holder and at least one robotic arm to manipulate items in or out of the bin. The mobile device holder secures a user mobile device which is communicatively coupled with the robotic cart. The robotic cart performs item manipulations based on data communicated from the coupled user device

A robotic post includes a processor and a memory. The robotic post may include a manipulation arm and a swiveling or otherwise movable trunk or base. One or more sensors provided on the robotic post enable the robotic post to determine the position and location of a piece of luggage. The processor, based on the sensor input, causes the robotic post to rotate, tilt or move toward the luggage to orient and secure a hook or gripper onto the handle of the luggage. The post may move, under control of the processor, to another location. When presented with authorization by a user, the luggage is released at the second location.

An integrated intelligent system includes a first intelligent electronic device, a second intelligent electronic device, a transferable intelligent control device (TICD) and a cross product bus. The first intelligent electronic device performs a first function and the second intelligent electronic device performs a second function. The cross product bus couples the first intelligent electronic device to the transferable intelligent control device. The TICD partially controls behaviors of the intelligent electronic device by sending commands over the cross product bus to the first intelligent electronic device and the TICD partially controls behaviors of the second intelligent electronic device to perform the second function. The TICD is first attached to the first intelligent electronic device to partially control the behaviors of the first electronic device, then detached from the first electronic device, and then attached to the second intelligent electronic device to perform the second function.

The present disclosure relates to the field of modular robot control, and more particularly, to a method for controlling a modular robot and a system thereof. The method includes the following steps: T1: providing a plurality of module units; T2: assembling the plurality of module units into an initial entity structure; T3: acquiring initial virtual configuration information of the initial entity structure; T4: generating an initial virtual configuration based on the initial virtual configuration information; T5: setting an action frame to generate preset action control information; and T6: transmitting the preset action control information to the modular robot which executes a motion according to the preset action control information.

A flux sensing system includes a memory and a processor in communication with the memory and at least one sensing device, the memory storing a plurality of published semantic fluxes associated with a plurality of location-based endpoints and/or item container devices. The flux sensing system is configured to apply semantic analysis to the sensing device inputs and semantic fluxes publishing and further control the publishing between semantic fluxes.

A robotic post system includes one or more robotic posts having a processor and a memory. The robotic posts may include a manipulation arm and/or a swiveling and/or otherwise moveable trunk and/or base. Sensors provided on the robotic post enable the robotic post to rotate, tilt or move toward another robotic post to orient and secure a lockable band on one post with a lock on another post. A manipulation arm may grasp a lockable band and attach it to a lock, and either post may move away from the other to extend the length of a guide path.

A multi-operation unit integration device having scale expandability and includes a plurality of operation units each of which includes a movable unit; and an integration module. The integration module includes an operation timing unit that gives operation timings of the plurality of operation units based on an operation instruction input from an outside, and the operation unit includes: a plurality of operation learning units that generate a control signal given to the movable unit according to an operation timing signal from the operation timing unit of the integration module; drive means for driving the movable unit of the operation unit according to the control signal; and a sensor that detects a state quantity of the movable unit driven by the drive means. An autonomous learning type robot device is configured using the multi-operation unit integration device as a control portion.

A robotic system includes at least two Hardware Modules, each having at least one sensor for measuring an internal property, a communication unit, a data storage unit and an embedded controller. The embedded controller is configured to collect collected data including status data representing the current status of the Hardware Module; and operating data representing usage of the Hardware Module. At least part of the collected data is determined from sensor data, and the embedded controller is configured to store or transmit the collected data. The robotic system including a central computation and command unit configured to receive the collected data; and to control operation of the robotic system by controlling operation of at least one actuator of the at least two Hardware Modules.

A robotic system includes at least two Hardware Modules, each having at least one sensor for measuring an internal property, a communication unit, a data storage unit and an embedded controller. The embedded controller is configured to collect collected data including status data representing the current status of the Hardware Module; and operating data representing usage of the Hardware Module. At least part of the collected data is determined from sensor data, and the embedded controller is configured to store or transmit the collected data. The robotic system including a central computation and command unit configured to receive the collected data; and to control operation of the robotic system by controlling operation of at least one actuator of the at least two Hardware Modules.

A method includes receiving, from a camera disposed on a robotic device, a two-dimensional (2D) image of a body of an actor and determining, for each respective keypoint of a first subset of a plurality of keypoints, 2D coordinates of the respective keypoint within the 2D image. The plurality of keypoints represent body locations. Each respective keypoint of the first subset is visible in the 2D image. The method also includes determining a second subset of the plurality of keypoints. Each respective keypoint of the second subset is not visible in the 2D image. The method further includes determining, by way of a machine learning model, an extent of engagement of the actor with the robotic device based on (i) the 2D coordinates of keypoints of the first subset and (ii) for each respective keypoint of the second subset, an indicator that the respective keypoint is not visible.