An autonomous mobile robot includes a first arithmetic unit configured to calculate a course direction based on an own position, a moving-object position, and a moving-object velocity vector, the course direction being a direction in which the autonomous mobile robot should travel, a second arithmetic unit configured to input the own position, the moving-object position, the moving-object velocity vector, and the course direction into a trained model and thereby calculate an estimated position, the trained model being a model that has been trained, the estimated position being a position at which the autonomous mobile robot is estimated to arrive a predetermined time later without colliding with the moving object, a generating unit configured to generate a remaining route from the estimated position to a destination, and a movement control unit configured to control a movement to the destination based on the course direction and the remaining route.

A method for automatic obstacle avoidance of a robot includes: obtaining distance values between the robot and an obstacle detected by sensors arranged on a left side, middle part and right side of the robot respectively; when a minimum distance value detected by the sensors on the middle part is less than a threshold value, if a minimum distance value detected by the sensors on either the left side or the right side exceeds an obstacle critical distance, turning the robot 90 degrees towards the side where the minimum distance value exceeds the obstacle critical distance; when the minimum distance value detected by the sensors on the middle part exceeds the distance threshold value, if only the minimum distance value detected by the sensors on the left side exceeds the obstacle critical distance, turning the robot towards the left side by a first angle value.

The present invention provides a method for automatic obstacle avoidance of a robot, and this method comprises: according to a depth sensor, obtaining depth data of movable areas of a scene in which the robot lies in; according to a preset depth threshold value, binarizing the depth data; according to an average value or a sum value of binarization processing result of areas, identifying an area where the robot is farther away from an obstacle as a moving direction of the robot. In the present invention, since the depth data is collected, no measurement dead zone is prone to occur; moreover, calculating the average value or the sum value of the binarized depth data only needs to perform a simple comparison, the processing is simpler, the processing speed is fast, and the requirement of the system and the cost are lower.

Systems and methods for object guidance and collision avoidance are provided. One system includes a location sensor disposed on a movable crane. The system also includes a plurality of sensors disposed on a plurality of objects within a facility. The system further includes a controller having a receiver for monitoring signals transmitted from the location sensor disposed on a movable crane and the plurality of sensors disposed on a plurality of objects within the facility. The controller is configured to generate a travel path for the movable crane to move an object coupled with the movable crane based on the one or more intersection regions and generate an output signal to an alarm device to provide an alert, when at least one object of the plurality of objects is within a predetermined proximity of at least the object being moved by the crane.

A cover for an automated robot includes elastic sheets that are adhered to each other in a geometry. The geometry is configured to allow the elastic sheets to expand and contract while the automated robot moves within its range of motion. The elastic sheets are attached to the automated robot by elasticity of the elastic sheets. A first group of the elastic sheets forms an elastic collar configured to grip the automated robot at a distal end and a proximal end of the cover in a non-breakable manner such that during operation of the robot, the elastic sheets hold their elasticity and integrity without breaking.

A robot control device includes a camera configured to be attached to a display device carried by or put on an operator and capture an environment surrounding the operator to generate an image of the environment; and a processor configured to slow down or stop motion of a predetermined robot included in the environment when the predetermined robot is not displayed on the display device, when only a portion of the predetermined robot is displayed, or when a ratio of a region representing the predetermined robot to a display area of the display device is equal to or lower than a predetermined threshold.

In various embodiments, safe robot operation is achieved by combining commercial, off-the-shelf, safety-rated components with the inherent safety-design mechanism of the robot to provide various allowable power levels to robotic actuators and thereby limit the forces and/or speeds generated by robotic appendages driven by the actuators.

A control device: includes a data acquiring unit to acquire inference data including moving speed information indicating a moving speed of an autonomous mobile object, relative position information indicating a relative position of a dynamic obstacle with respect to the autonomous mobile object, and relative speed information indicating a relative speed of the dynamic obstacle with respect to the autonomous mobile object; a control amount calculating unit to calculate a control amount for controlling movement of the autonomous mobile object depending on movement of the dynamic obstacle using the inference data or preprocessed inference data corresponding to the inference data, and a control unit to control the movement of the autonomous mobile object using the control amount. The control amount calculating unit uses a learned model by machine learning, and the learned model receives an input of the inference data or the preprocessed inference data and outputs the control amount.

A robot sensor arrangement system. At least one sensor assembly is arranged on a robot body (20), wherein the sensor assembly comprises image sensors (1001, 1002) and a first inertial sensor (1007), and the positions of the image sensors (1001, 1002) relative to the first inertial sensor (1007) are fixed such that the image sensors and the first inertial sensor (1007) do not move as external physical conditions, such as vibration and temperature change. The included angle between the positions of the image sensors (1001, 1002) and a vertical axis is in a first angle range so as to ensure the robot can autonomously sense the surrounding environment to improve the capability of autonomous obstacle avoidance and the robustness of a robot system.

A device for indicating appropriate social distancing includes the ability to project light (in various forms and in a various ways) onto the ground in a manner visible by the user and those around them. A boundary of the projected light can be set to an acceptable social distance and can include different colors to indicated varying social distances for varying levels of trusted individuals. Proximity sensors set to appropriate distancing requirements, along with the varying levels of trust can be implemented into multiple devices being used in a group setting.