Smart warehousing and receiving goods

Natural navigation unmanned AGV

The pallet handling operation is to transport the whole pallet cargo from the transport vehicle to the receiving area for quality inspection and storage. Currently, the automation solution uses a laser or inertial navigation unmanned AGV for pallet handling operations. These unmanned AGVs are usually equipped with reflectors, magnetic nails and other markers or reflectors in a fixed area. The working environment is fixed and the working condition is stable. It is the most mature and perfect warehouse automation solution. Based on the traditional laser navigation AGV, it is dedicated to the development of SLAM (simultaneous positioning and map creation) technology to realize the natural navigation of unmanned AGV. It does not need to install markers or reflectors, just need to install the environment-aware sensor. The human AGV starts from a certain location in an unknown environment, and performs self-positioning according to the sensing information acquired by the internal and external sensors during the movement process, and gradually establishes a continuous environment map, and then can realize the unmanned forklift on the basis of the map. Accurate positioning and path planning to complete navigation tasks. The natural navigation unmanned AGV has the characteristics of short installation time, low input cost, and free creation of new paths. It is an excellent research and development direction for the next generation of intelligent unmanned AGV.


Intelligent demolition robot

The unpacking operation is to carry a box of goods placed on the transfer tray to the conveyor line. The traditional automation solution is completed by the industrial robot arm grabbing or sucking. Because the industrial robot arm operation control is based on the box size and palletizing rules stored in the computer system database, and the on-site job object is not recognized online, it can only be realized. The removal of the same size of the box from the same tray, the maintenance of the database is a very arduous task when faced with thousands of types of cargo boxes. The size of the cargo boxes on the same pallet received by the e-commerce company is different, and there is no fixed rule in the pallet. The traditional industrial robot arm is difficult to operate. The intelligent demolition robot uses 3D vision and deep learning algorithms to realize self-training and self-correction of industrial robot arm operations, without the need for box and 的 type database maintenance. The industrial robot recognizes the top cargo contour through a 3D depth camera. When picking up a box for the first time, it builds a model of the shape of the box and accelerates the identification of the next box based on this model.

Reprinted from the network