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.

Provided are a container storage system, a warehousing system, a robot control method, and a robot; the container storage system comprises an inventory area, a control server, a robot, and a plurality of workstations; the control server communicates with the robot wirelessly; an inventory rack is placed in the inventory area; the inventory rack comprises at least one layer of layered panels; the at least one layer of layered panels divides the inventory rack into at least two layers; at least two storage containers are placed on the inventory rack in the direction of the depth of the layered panels, and the direction of width of the storage container on the inventory rack is consistent with the direction of the depth of the layered panels. The system increases the storage density of storage containers in the inventory area, and reduces the energy consumption of the robot picking the storage containers.

A UV based surface disinfection system that consists of the UV light source, a robot arm, and an omni directional mobile base. The mobile robot can be programmed autonomously and be able to bring the UV light source to the centimeters away from surfaces to achieve effective and efficient surface disinfection. The mobile robot can navigate autonomously in a complicated environment to perform disinfection operation in a large area.

A robot apparatus is provided on a stand and includes a control apparatus that controls the robot apparatus. The control apparatus calculates vibration generated on the stand based on model data of the stand and trajectory data of an operation of the robot apparatus and corrects the trajectory data based on the vibration.

A robot system includes a robot arm driven by an electric motor and a vehicle that is movable and supports the robot arm. A control method includes (a) moving the vehicle to a work station of a first type and (b) driving the robot arm in the work station of the first type. The (a) executes a first operation mode for, in a part of the movement to the work station of the first type, moving the vehicle in a state in which electric power is not supplied to the electric motor, starting supply of the electric power to the electric motor during the movement of the vehicle in the state in which the electric power is not supplied to the electric motor, and arranging the vehicle in the work station of the first type in a state in which the electric power is supplied to the electric motor.

A computing device performs computation for controlling operations of a mobile manipulator configured to hold a plurality of target objects with a manipulator and move the target objects to predetermined positions. The computing device includes a storage and a calculator. The storage stores a trained machine learning model trained by inputting a plurality of training data sets, which are combinations of state variables and pieces of determination data associated with the state variables. The training data sets are acquired in advance. The calculator outputs a movement-target object to be moved to a predetermined position at current time by inputting the state variable to the trained machine learning model read from the storage. The state variable contains relative positions of the target objects to a specific portion of the mobile manipulator. The determination data associated with the state variable represents the movement-target object.

Systems and methods for process tending with a robot arm are presented. The system comprises a robot arm and robot arm control system mounted on a self-driving vehicle, and a server in communication with the vehicle and/or robot arm control system. The vehicle has a vehicle control system for storing a map and receiving a waypoint based on a process location provided by the server. The robot arm control system stores at programs that is executable by the robot arm. The vehicle control system autonomously navigates the vehicle to the waypoint based on the map, and the robot arm control system selects a target program from the stored programs based on the process location and/or a process identifier.

A computer-implemented method executed by data processing hardware of a robot causes the data processing hardware to receive sensor data associated with a door. The data processing hardware determines, using the sensor data, door properties of the door. The door properties can include a door width, a grasp search ray, a grasp type, a swing direction, or a door handedness. The data processing hardware generates a door movement operation based on the door properties. The data processing hardware can execute the door movement operation to move the door. The door movement operation can include pushing the door, pulling the door, hooking a frame of the door, or blocking the door. The data processing hardware can utilize the door movement operation to enable a robot to traverse a door without human intervention.

A position and tracking system for radio-based localization in an operating room, includes a receiver, a mobile cart, a processor, and a memory coupled to the processor. The mobile cart includes a robotic arm and a transmitter in operable communication with the receiver. The memory has instructions stored thereon which, when executed by the processor, cause the system to receive, from the transmitter, a signal including a position of the mobile carts in a 3D space based on the signal communicated by the transmitter and determine a spatial pose of the mobile carts based on the received signal.

A method includes receiving sensor data representative of surfaces in a physical environment containing an interaction point for a robotic device, and determining, based on the sensor data, a height map of the surfaces in the physical environment. The method also includes determining, by inputting the height map and the interaction point into a pre-trained model, one or more candidate positions for a base of the robotic device to allow a manipulator of the robotic device to reach the interaction point. The method additionally includes determining a collision-free trajectory to be followed by the manipulator to reach the interaction point when the base of the robotic device is positioned at a selected candidate position of the one or more candidate positions and, based on determining the collision-free trajectory, causing the base of the robotic device to move to the selected candidate position within the physical environment.