Visionnav Robotics USA Inc.

Visionnav Robotics (shenzhen) Co., Ltd.

Mu Fang

Hao Jia Li

Bo Li

Yujie Lu

Bingchuan Yang

Peng Chen

Lisha Huang

Hang Ding

Luyang Li

The disclosure relates to a method for warehouse storage-location monitoring, a computer device, and a storage medium. The method includes the following. Video data of a warehouse storage-location area is obtained, and a target image corresponding to the warehouse storage-location area is obtained based on the video data, where the warehouse storage-location area includes an area of a storage-location and an area around the storage-location. The target image is detected based on a category detection model, to determine a category of each object appearing in the target image. A detection result is obtained by detecting a status of each object based on the category of each object. The detection result is transmitted to a warehouse scheduling system, where the detection result is used for the warehouse scheduling system to monitor the warehouse storage-location area.

Method for warehouse storage-location monitoring, computer device, and non-volatile storage medium

A method for cargo counting, a computer equipment, and a storage medium are provided in the disclosure. The method includes the following. Three-dimensional (3D) point cloud data of a set of cargoes within a preset placement region is obtained based on a cargo-counting instruction. Whether the set of cargoes are in a first placement state is determined according to the 3D point cloud data. Based on a determination that the set of cargoes are in the first placement state, a quantity of the set of cargoes is calculated.

Method for cargo counting, computer equipment, and storage medium

A method and apparatus for forklift pickup, a computer device, and a storage medium are provided in the disclosure. The method includes the following. Observational data of a truck parking area is obtained by observing the truck parking area. Point cloud data of at least one truck is obtained in the observational data, and point cloud data of each of the at least one carrier is obtained in the point cloud data of the at least one truck. A relative pose of each of at least one carrier is determined based on the point cloud data of each of the at least one carrier. A pickup priority is determined based on the point cloud data of each of the at least one carrier. A forklift is controlled to perform pickup according to the relative pose of each of the at least one carrier and the pickup priority.

Method for forklift pickup, computer device, and non-volatile storage medium

A method for determining material-cage stacking, a computer device, and a storage medium are provided. The method includes the following. A material-cage image is obtained by photographing a first stacking apparatus of a first material cage and a second stacking apparatus of a second material cage. The stacking apparatuses of the two material cages in the material-cage image can be recognized respectively with two detection models. The first stacking result is obtained by obtaining location information of the stacking apparatuses of the two material cages with the first detection model, and the second stacking result is obtained with the second detection model.

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Guangdong, China

Mu Fang