Abstract: Exfoliated nanoplatelets functionalized with a non-polar moiety, such as an ethylene or propylene derived polymer, are useful for forming composites, films, and polymer blends.

Abstract: A cooling structure includes a base with a plate shape, that extends in a first direction along a refrigerant flow direction and in a second direction perpendicular or substantially perpendicular to the first direction, a thickness of which extending in a third direction perpendicular or substantially perpendicular to the first direction and the second direction, and fins that protrude from the base to one side in the third direction, that extend in the first direction, and that are side by side in the second direction. Each of the fins includes a curved portion that is curved due to a convex portion, protruding to one side in the second direction, and a concave portion, recessed from the other side to the one side in the second direction, located at a same position in the first direction.

Abstract: A method for obstacle detection and recognition for an intelligent snow sweeping robot is disclosed, comprising: 1) disposing ultrasonic sensors at a front end of the snow sweeping robot to detect distance information from an obstacle ahead; and disposing radar sensors at the front and rear of the snow sweeping robot to detect whether a creature suddenly approaches; 2) processing signals detected by each of the ultrasonic sensors and radar sensors, and calculating a forward distance of the snow sweeping robot; and 3) determining a snow cover extent of a working road, detecting a change of the distance from the obstacles, and recognizing the obstacles for conditions of an ultrasonic ranging variation ratio and a variation of the forward distance of the snow sweeping robot, a change of the signal detected by radar sensors, and a descriptive statistic of the snow cover extent within a specific time period.

Abstract: The present disclosure discloses a neural network adaptive tracking control method for joint robots, which proposes two schemes: robust adaptive control and neural adaptive control, comprising the following steps: 1) establishing a joint robot system model; 2) establishing a state space expression and an error definition when taking into consideration both the drive failure and actuator saturation of the joint robot system; 3) designing a PID controller and updating algorithms of the joint robot system; and 4) using the designed PID controller and updating algorithms to realize the control of the trajectory motion of the joint robot. The present disclosure may solve the following technical problems at the same time: the drive saturation and coupling effect in the joint system, processing parameter uncertainty and non-parametric uncertainty, execution failure handling during the system operation, compensation for non-vanishing interference, and the like.

Abstract: A snow shovel structure of a snow plow robot. The snow shovel structure includes a housing where a snow shovel mechanism is. The snow shovel mechanism extends outside the housing and includes a first motor fixed on a top of the housing. The first motor is fixedly connected with a telescopic rod through an output shaft. A second motor is further provided on a top portion of an inner chamber of the housing, and a horizontal plate is fixedly arranged on a side wall of the inner chamber of the housing.

Abstract: An image detection device and an image detection method are provided. The image detection method includes: obtaining an image, where the image includes an object; adjusting a first size of the image to generate an adjusted image; generating a first divided image and a second divided image according to the image; and detecting the object in the image based on a plurality of input images, where the plurality of input images includes the first divided image, the second divided image, and the adjusted image.

Abstract: Disclosed is a snow shoveling and snow discharging assembly of a snow sweeping robot. The snow shoveling and snow discharging assembly comprises a snow stirring structure, a snow feeding structure and a snow raising structure. Stirring cutters in the snow stirring mechanism are driven by a stirring cutter shaft to stir bottom area snow into a snow feeding pipe of the snow feeding structure, an air blower in the snow feeding structure blows accumulated snow into a snow raising pipe of the snow raising structure through a connecting pipe, the snow raising pipe can be driven by a steering motor to rotate by a certain angle to control the snow raising direction, and a second electric push rod acts to control pitching of the guide part, so that the height of snow during snow raising is controlled.

Abstract: A snow shovel structure of a snow plow robot is provided. The snow shovel structure includes a housing where a snow shovel mechanism is. The snow shovel mechanism extends outside the housing and includes a first motor fixed on a top of the housing. The first motor is fixedly connected with a telescopic rod through an output shaft. A second motor is further provided on a top portion of an inner chamber of the housing, and a horizontal plate is fixedly arranged on a side wall of the inner chamber of the housing.

Abstract: The present disclosure provides a neural network-based visual detection and tracking method of an inspection robot, which includes the following steps of: 1) acquiring environmental images of a dynamic background a movement process of the robot; 2) preprocessing the acquired images; 3) detecting human targets and specific behaviors in the images in the robot body, and saving the sizes, position information and features of the human targets with the specific behaviors; 4) controlling the orientation of a robot gimbal by using a target tracking algorithm to make sure that a specific target is always located at the central positions of the images; and 5) controlling the robot to move along with a tracked object. The neural network-based visual detection and tracking method of an inspection robot in the present disclosure has a quite high adaptive ability, achieves better detection and tracking effects on targets in a dynamic background scene.

Abstract: The present disclosure provides a neural network-based visual detection and tracking method of an inspection robot, which includes the following steps of: 1) acquiring environmental images of a dynamic background a movement process of the robot; 2) preprocessing the acquired images; 3) detecting human targets and specific behaviors in the images in the robot body, and saving the sizes, position information and features of the human targets with the specific behaviors; 4) controlling the orientation of a robot gimbal by using a target tracking algorithm to make sure that a specific target is always located at the central positions of the images; and 5) controlling the robot to move along with a tracked object. The neural network-based visual detection and tracking method of an inspection robot in the present disclosure has a quite high adaptive ability, achieves better detection and tracking effects on targets in a dynamic background scene.

Abstract: A method for obstacle detection and recognition for an intelligent snow sweeping robot is disclosed, comprising: 1) disposing ultrasonic sensors at a front end of the snow sweeping robot to detect distance information from an obstacle ahead; and disposing radar sensors at the front and rear of the snow sweeping robot to detect whether a creature suddenly approaches; 2) processing signals detected by each of the ultrasonic sensors and radar sensors, and calculating a forward distance of the snow sweeping robot; and 3) determining a snow cover extent of a working road, detecting a change of the distance from the obstacles, and recognizing the obstacles for conditions of an ultrasonic ranging variation ratio and a variation of the forward distance of the snow sweeping robot, a change of the signal detected by radar sensors, and a descriptive statistic of the snow cover extent within a specific time period.

Abstract: The present disclosure discloses a neural network adaptive tracking control method for joint robots, which proposes two schemes: robust adaptive control and neural adaptive control, comprising the following steps: 1) establishing a joint robot system model; 2) establishing a state space expression and an error definition when taking into consideration both the drive failure and actuator saturation of the joint robot system; 3) designing a PID controller and updating algorithms of the joint robot system; and 4) using the designed PID controller and updating algorithms to realize the control of the trajectory motion of the joint robot. The present disclosure may solve the following technical problems at the same time: the drive saturation and coupling effect in the joint system, processing parameter uncertainty and non-parametric uncertainty, execution failure handling during the system operation, compensation for non-vanishing interference, and the like.

Abstract: An image detection device and an image detection method are provided. The image detection method includes: obtaining an image, where the image includes an object; adjusting a first size of the image to generate an adjusted image; generating a first divided image and a second divided image according to the image; and detecting the object in the image based on a plurality of input images, where the plurality of input images includes the first divided image, the second divided image, and the adjusted image.

Abstract: A fastening device includes a fixing nut and a fixing base. The fixing base includes a base plate, an anti-falling wall, a door piece, and an anti-tilt arm. The anti-falling wall, the door piece and the anti-tilt arm are formed on the base plate, and the anti-tilt arm is arranged opposite to the door piece. An accommodation space is formed between the anti-falling wall, the door piece and the anti-tilt arm, and the fixing nut is rotatably arranged in the accommodation space. In addition, a heat dissipation module with the fastening device is also disclosed herein.

Abstract: An image generating method and an electronic apparatus are provided. The method includes: determining whether at least one object in a plurality of first images to be captured will generate a blur to generate a determination result; determining a first amount of at least one second image in the plurality of first images and a second amount of at least one third image in the plurality of first images according to the determination result, wherein a first setting for capturing the second image is different from a second setting for capturing the third image; capturing the second image according to the first setting; capturing the third image according to the second setting; using the first amount of the second image and the second amount of the third image to perform an image superposition operation to generate an output image; and outputting the output image.

Abstract: A multi-camera electronic device and a control method thereof are proposed. The method includes the following steps. At least one camera of the electronic device is used for scene detection to generate photographing analysis information. All the photographing analysis information is collected, and joint photographing information including a joint target is generated through a communication process among all the cameras. An individual photographing parameter of each camera is generated according to the joint photographing information. Each camera is controlled to capture an image of the scene by using its individual photographing parameter to respectively generate a corresponding output image.

Abstract: An image generating method and an electronic apparatus are provided. The method includes: determining whether at least one object in a plurality of first images to be captured will generate a blur to generate a determination result; determining a first amount of at least one second image in the plurality of first images and a second amount of at least one third image in the plurality of first images according to the determination result, wherein a first setting for capturing the second image is different from a second setting for capturing the third image; capturing the second image according to the first setting; capturing the third image according to the second setting; using the first amount of the second image and the second amount of the third image to perform an image superposition operation to generate an output image; and outputting the output image.

Abstract: A three-dimensional sensing apparatus including a light-projecting device, at least two image-capture devices, and a processor is provided. The processor is electrically connected to the light-projecting device and the at least two image-capture devices and adapted to provide a control signal to the light-projecting device to adjust the intensity of the illumination beam. The processor adjusts the contrast of the captured image to form a contrast-enhanced image according to a first processing signal and extracts a feature region of the contrast-enhanced image to form a feature-extraction image according to a second processing signal. The processor normalizes the intensity of the feature-extraction image to form an optimized image according to a third processing signal and forms the optimized image into a depth image according to a sensing signal.

Abstract: An image processing method and an image processing device are provided. The image processing method includes: obtaining images and calculating depth information corresponding to the images via a processor; segmenting each of the images into a foreground area and a background area according to color information, brightness information, and the depth information of the images via the processor; obtaining the foreground area of a first image of the images via the processor, wherein a brightness of the foreground area of the first image is greater than a first threshold; obtaining the background area of a second image of the images via the processor, wherein a brightness of the background area of the second image is less than a second threshold; and fusing the foreground area of the first image and the background area of the second image via the processor to generate a high dynamic range image.

Abstract: A stereo image generating method and an electronic apparatus utilizing the method are provided. The electronic apparatus includes a first camera and a second camera capable of capturing stereo images, and a resolution of the first camera is larger than that of the second camera. In the method, a first image is captured by the first camera, and a second image is captured by the second camera. The second image is upscaled to the resolution of the first camera, and a depth map is generated with use of the first image and the upscaled second image. With reference to the depth map, the first image is re-projected to reconstruct a reference image of the second image. An occlusion region in the reference image is detected and compensated by using the upscaled second image. A stereo image including the first image and the compensated reference image is generated.