A robotic door lock includes a lockable spinner having a spinner shell coupled to a bolt rail and an axial profile coupled to a door handle or knob. A processor selectively engages the spinner shell with the axial profile via an actuator to enable the manipulation of the bolt. The robotic lock has a wireless module, an actuator, and a processor in communication with the actuator and a wireless module. The wireless module uses a wireless energy harvester configured to receive energy from a user device or a post infrastructure to power the processor, the actuator and the memory. The wireless energy harvester may be connected to an internal energy storage.

Provided is a robot including a chassis; a set of wheels coupled to the chassis; a plurality of sensors; a processor; and a tangible, non-transitory, machine readable medium storing instructions that when executed by the processor effectuates operations. The operations include capturing, with an image sensor disposed on the robot, a plurality of images of an environment of the robot as the robot navigates within the environment; identifying, with the processor, an obstacle type of an obstacle captured in an image based on a comparison between features of the obstacle and features of obstacles with different obstacles types stored in a database; and determining, with the processor, an action of the robot based on the obstacle type of the obstacle.

A Hardware Module for a robotic system includes at least one sensor for measuring an internal property of the Hardware Module, a communication unit for communicating with other Hardware Modules, a data storage unit and an embedded controller. The embedded controller is configured to collect collected data, the collected data including: status data representing the current status of the Hardware Module; and operating data representing usage of the Hardware Module wherein at least part of the collected data is determined from sensor data from the at least one sensor, and the embedded controller is configured to perform at least one of: storing the collected data on the data storage unit; and transmitting the collected data via the communication unit.

The present disclosure relates to a module-type robot control system comprising: a robot platform including a driving unit which is driven by a control signal, at least one function block which is assemblable and disassemblable on the robot platform and configured to perform a specific function, and a user terminal capable of wirelessly communicating with the robot platform and the function block. According to the system. The user may remotely control the module-type robot through a smart device, or receive related content by receiving data from the robot through the terminal. The user may easily control the robot or receive more diverse customized contents by connection between the smart device and the module-type robot system.

A robotic post includes a memory and a processor in communication with the memory, an optical sensor, a support holder and a securable hook. The robotic post is configured to secure an item container by coupling it to the securable hook and further adjusting the support holder. An optional robotic arm manipulates items in or out the item container based on particular semantics of interest inferred based on inputs from the optical sensor.

A plurality of robotic posts each include at least one processor, a memory and at least one divider panel secured to the post through a securable latch controlled through the at least one processor. A robotic post may move to a divider location to enforce access control between a first region and a second region divided, at least partially, by its at least one divider panel.

The invention relates to a method for controlling a robotic device (50) with modified control commands transmitted over a wireless network, wherein the robotic device (50) comprises a plurality of joints (53), wherein each joint represents one degree of freedom of the robotic device, the method comprising at a trajectory modification entity (100): -determining a load of the wireless network (30), -receiving a plurality of control commands controlling a planned trajectory of the robotic device (50) from a robotic control entity (70), each of the control commands configured to control one degree of freedom of a first number of degrees of freedom addressed by the plurality of control commands, -determining a reduced number of degrees of freedom for the modified control commands smaller than the first number based on the determined load, -determining the modified control commands based on the reduced number of degrees of freedom, wherein the modified control commands address a limited number of degrees of freedom not higher than the reduced number of degrees of freedom, -transmitting the modified control commands instead of the received plurality of control commands to the robotic device (50).

A mobile robotic device includes a mobile base and a mast fixed relative to the mobile base. The mast includes a carved-out portion. The mobile robotic device further includes a three-dimensional (3D) lidar sensor mounted in the carved-out portion of the mast and fixed relative to the mast such that a vertical field of view of the 3D lidar sensor is angled downward toward an area in front of the mobile robotic device.

A display control system includes a sensor and a wireless transceiver, with a display controller and memory storing a plurality of endpoints. The memory further stores a plurality of semantic identities and is configured for communication with a mobile device. The display controller receives from the mobile device a semantic profile, and infers a first person semantic gesture and a second person semantic gesture. The display control system controls access to a user interface by determining that the semantic gestures are applicable to the semantic identity based on a semantic drift, and either allows or disallows access to manipulation of the user interface.

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.