The invention relates to a delivery system having a delivery goods vehicle for delivering inward goods, and having at least one automated transfer assembly which for transferring the goods in an automated manner from the delivery goods vehicle to a goods store comprises an object detection device. The delivery system moreover has a safety installation for securing a movement range of the transfer assembly when unloading the goods.

Carpet detection using an RGB-D camera and mobile machine movement control based thereon are disclosed. Carpets and carpet curls are detected by obtaining a RGB-D image pair including an RGB image and a depth image through an RGB-D camera, detecting carpet and carpet-curl areas in the RGB image and generating a 2D bounding box to mark each area using a deep learning model, and generating groups of carpet and carpet-curt points corresponding to each of the carpet and carpet-curl areas by matching each pixel of the RGB image within each 2D bounding box corresponding to the carpet and carpet curl areas to each pixel in the depth image.

Disclosed herein is a robot stopping parallel to an installed object and a method of stopping the same. In the robot stopping parallel to an installed object, a pause state of the robot is determined, and when an obstacle sensor calculates distances from obstacles, the robot moves such that the robot is placed parallel and close to an adjacent one of installed objects disposed around the robot.

A robot can include a cart to receive one or more objects; a camera sensor to photograph a periphery of the robot and capture an image of a user of the robot; a handle assembly coupled to the cart; a moving part to move the robot; a force sensor to sense a force applied to the handle assembly; and a controller configured to generate physical characteristics information on physical characteristics of the user of the robot based on the image of the user, and adjust at least one of a moving direction of the robot, a moving speed of the moving part and a value of torque applied to a motor of the moving part, based on the physical characteristics information and a magnitude of the force applied to the handle assembly sensed by the force sensor.

A control device and a control method can quickly estimate a self-location even when the self-location is unknown. In a case of storing information supplied in a time series detected by LIDAR or a wheel encoder and estimating a self-location by using the stored time-series information, when a position change happens unpredictably in advance such as a kidnap state is detected, the stored time-series information is reset, and then the self-location is estimated again. Example host platforms include a multi-legged robot, a flying object, and an in-vehicle system that autonomously moves in accordance with a mounted computing machine.

A control apparatus for an auto clean machine comprising a light source configured to emit light to illuminate at least one light region outside and in front of the auto clean machine. The control apparatus comprises: a first image sensing area, configured to sense a first brightness distribution of the light region, wherein a resolution for a first direction of the first image sensing area is higher than a resolution for a second direction of the first image sensing area; and a processor, configured to control movement of the auto clean machine according the first brightness distribution.

A robotic cleaner may include a body, an optical receiver, the optical receiver being configured to detect an optical signal generated by an external device, and an optical pattern generator configured to emit light according to an optical pattern that extends at least partially around the body, wherein, when the optical pattern intersects an obstacle, at least a portion of the light incident on the obstacle is reflected towards the optical receiver, the optical receiver being configured to detect the reflected light.

A method of obstacle handling for a mobile automation apparatus includes: obtaining an initial localization of the mobile automation apparatus in a frame of reference; detecting an obstacle by one or more sensors disposed on the mobile automation apparatus; generating and storing an initial location of the obstacle in the frame of reference, based on (i) the initial localization, and (ii) a detected position of the obstacle relative to the mobile automation apparatus; obtaining a correction to the initial localization of the mobile automation apparatus; and applying a positional adjustment, based on the correction, to the initial position of the obstacle to generate and store an updated position of the obstacle.

A robot cleaner and a control method thereof are disclosed. A robot cleaner, according to an embodiment of the present invention, comprises: a tilt sensor module; a distance sensor module; and a light amount sensor module. Each piece of sensed information is transmitted to a lifting information calculation module. The lifting information calculation module calculates information on whether the robot cleaner is lifted, by using each piece of the transmitted information. If it is calculated that the robot cleaner is lifted off a floor, a power module is stopped. In addition, if it is calculated that the robot cleaner is not lifted off the floor, the power module is driven. Accordingly, when a user lifts the robot cleaner, injuries to the user caused by operation of a drive module can be prevented.

A conveyance robot includes a main body at which a conveyed object can be placed; a driving wheel provided at the main body; a memory; and a processor coupled to the memory. The processor is configured to control the driving wheel such that a progress direction of the conveyance robot is configured to match an extension direction of a running path guide portion, the running path guide portion extending along a running path that is along a wall face of a wall disposed in a building.