Abstract: An autonomous mobile robot fleet includes a service transceiver module, a dispatch module, a robot fleet, a monitoring module, a storage module, and a certificate module. The service transceiver module is configured to receive and send mission information. The dispatch module couples to the service transceiver module, and is configured to generate dispatch information according to the mission information. The robot fleet wirelessly couples to the dispatch module. The robot fleet is used to execute the dispatch information. The monitoring module wirelessly couples to the robot fleet. The monitoring module generates monitoring information according to a status signal from the robot fleet. The storage module couples to the dispatch module and the monitoring module. The certificate module couples to the storage module, and wirelessly couples to the robot fleet. The certificate module is configured to generate certificate information according to the dispatch information and the monitoring information.

Abstract: A path planning method and an autonomous traveling robot are provided. In the path planning method, a target area is obtained. A traveling path is decided by a safety distance. The traveling path is at least at the safety distance from an edge of the target area. The autonomous traveling robot is controlled to move by the traveling path. Accordingly, the operation efficiency can be improved.

Abstract: An object detection device is provided in the invention. The object detection device includes an image-extraction device and a processor. The image-extraction device extracts a plurality of images and a plurality of depth images in a specific space, wherein each image corresponds to one of the depth images. The processor may detect objects in each image using an object detection model to obtain object information. The processor may calculate the depth value of each object in each depth image. The processor may input the depth value of each object into an object status model to determine the object status of each object. The processor may determine whether to enter the specific space based on the object information and the object status of each object. Therefore, the object detection device provided in the invention will be able to determine a suitable time to enter the specific space.

Abstract: A fish identification method is provided. The fish identification method includes capturing an image through a processor, wherein the image includes a fish image. The fish identification method includes identifying a plurality of feature points of the fish image through a coordinate detection model and obtaining a plurality of sets of feature-point coordinates. Each of the plurality of sets of feature-point coordinates corresponds to each of the plurality of feature points. The fish identification method further includes calculating a body length or an overall length of the fish image according to the plurality of sets of feature-point coordinates of the image.

Abstract: An image recognition method includes the following steps. An original image with a first resolution is received, and the first resolution of the original image is reduced to generate a low-resolution image with a second resolution. The first resolution is higher than the second resolution. The position of a target object in the low-resolution image is identified using an object detection model to obtain the target object coordinates in the low-resolution image. A target object image is segmented from the original image according to the target object coordinates in the low-resolution image, and the target object image is input into the image classification model. The target object type that corresponds to the target object image is determined using the image classification model.