The present technology relates to a control device, a control method, and a program that make it possible for objects that are capable of moving autonomously to move in corporation with each other. The control device according to one aspect of the present technology moves, in response to an action made by a user on a predetermined object among multiple objects that are capable of moving autonomously, an object corresponding with the predetermined object. The present technology can be applied to a control device that controls mobile robots.

This application relates to an autonomously navigating robot. In one aspect, the robot includes an end effector configured to measure a person's body temperature and, when the body temperature exceeds a standard fever temperature, activate a chatbot to check symptoms of Covid-19. The robot may also include a manipulator configured to align the end effector with the person's forehead. The robot may further include a mobile robot configured to detect the person and move the end effector and the manipulator to a position where the person is located by performing autonomous navigation.

The present application discloses an automated restaurant comprising: a kitchen; a customer-tracking area comprising a dining area; and a plurality of vehicles. The kitchen comprises a storage apparatus to store ingredient containers, a transfer apparatus to move ingredient containers, and one or more cooking stations. Each vehicle is configured to move one or more food containers from cooking stations to dining tables. A tracking system comprises cameras, lidars, etc., which are fixedly mounted. The tracking system can dynamically map out the fixtures, humans and vehicles in the restaurant. Information from the tracking system is used to control the motion of the vehicles. The tracking system can dynamically track the positions of customers in the customer-tracking area, so that foods ordered by specific customers may be automatically sent by vehicles to the customers' locations.

Systems and methods that employ an autonomous robotic vehicle (ARV) alone or in combination with a remote computing device during the installation of electronic shelf labels (ESLs) in a facility are discussed. The ARV may detect pre-existing product information from paper labels located on modular units prior to their removal and then detect the location of electronic shelf labels (ESLs) after installation. Pre-existing product information gleaned from the paper labels is associated with the corresponding ESLs. The ARV may also determine compliance or non-compliance of modular units to which an ESL is affixed with a planogram of the facility.

Disclosed herein are a method of localization using multi sensors and a robot implementing the same, the method including sensing a distance between an object placed outside of a robot and the robot and generating a first LiDAR frame by a LiDAR sensor of the robot while a moving unit moves the robot, capturing an image of an object placed outside of the robot and generating a first visual frame by a camera sensor of the robot, and comparing a LiDAR frame stored in a map storage of the robot with the first LiDAR frame, comparing a visual frame registered in a frame node of a pose graph with the first visual frame, determining accuracy of comparison's results of the first LiDAR frame, and calculating a current position of the robot by a controller.

A support assembly is provided. The support assembly includes: a lower frame configured to be mountable on one surface of a moving object; a guide frame configured such that one end is coupled to an upper surface of the lower frame, and at least a part of another end is curved toward where the lower frame is located; a connection frame configured such that one side includes a plurality of rollers spaced apart at a predetermined interval, and the plurality of rollers slide along the curved part of the guide frame; and an upper frame coupled to another side of the connection frame and configured to move in response to the plurality of rollers sliding along the curved part of the guide frame.

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.

The present invention relates to a robot service system and a robot apparatus using a social network service, and comprises: (a) a step in which a terminal device is connected to a robot apparatus by executing a social network service program, and displays a service screen on which an image captured by the robot apparatus is displayed; (b) a step in which the terminal device transmits a robot control command inputted to the service screen to the robot apparatus; (c) a step in which the robot apparatus performs an operation according to the robot control command and transmits operation performance data to the terminal device; and (d) a step in which the terminal device displays the operation performance data transmitted from the robot apparatus on the service screen.

One variation of a method for automatically generating a planogram for a store includes: dispatching a robotic system to autonomously navigate within the store during a mapping routine; accessing a floor map of the floor space generated by the robotic system from map data collected during the mapping routine; identifying a shelving structure within the map of the floor space; defining a first set of waypoints along an aisle facing the shelving structure; dispatching the robotic system to navigate to and to capture optical data at the set of waypoints during an imaging routine; receiving a set of images generated from optical data recorded by the robotic system during the imaging routine; identifying products and positions of products in the set of images; and generating a planogram of the shelving segment based on products and positions of products identified in the set of images.

A robot in accordance with at least some embodiments of the present technology is configured for bimanual manipulation of objects. The robot includes a body and two arms individually defining an arm length and including an end effector, an end effector joint proximally adjacent to the end effector along a kinematic chain corresponding to the arm, and a gripper proximal to the end effector along the arm length. The end effector joint is configured to rotate the end effector relative to the gripper. The robot is configured to move at least a portion of a bottom surface of an object away from a support surface by applying force to the object via frictional interfaces between convex gripping surfaces of the grippers and side surfaces of the object. This creates a gap into which paddles of the end effectors can be inserted to support the object from below.