Intelligent Picking Robot for Fully Automated Logistics
Based on the vision and intelligence technology we have developed for factory automation, we are introducing a complete logistics solution. We aim to:
- Open up a new application area for robots with vision and intelligence
- Free people from the manual labor inside factories and warehouses
- Revolutionize the manufacturing and logistics industries
Repacking of products
Also referred to as piece-picking, this requires the ability to distinguish a large variety of products and pick them one-by-one.
Our fully automated picking system eliminates mistakes and delays.
We provide a fully automated palletizing solution which human used to perform using experience and intuition.
Our palletized solution is optimized to be physically stable and reduce wasted space.
De-palletizing boxes of various sizes
We provide a fully automated solution that can de-palletize a pallet of mixed-size boxes.
Palletizing Automation using Intelligent Robot Download
Using our automated palletizing algorithm, a trolley is automated loaded with boxes. During palletizing, it is necessary to generate trajectories for the robot that avoid collision with obstacles while minimizing the cycle time. The above video shows a demonstration of the technology that we have developed.
Our palletizing algorithm provides:
- Loading as many boxes as possible
- Packing the boxes with minimum gaps
- Stacking that prevents collapse of the loaded boxes
- Stacking such that the top layer is as flat as possible
In the above simulation, given a random list of boxes, they are rearranged in the optimal order. Additionally, an animation of the palletized solution can be visualized.
Using our intelligent picking robots, people can be freed from arduous palletizing labor.
Piece-Picking Automation using Intelligent Robot Download
In the piece-picking of common household items, the ability to deal with a large variety of items with many different shapes is required. Using state-of-the-art image recognition technology, suitable grasp positions can be estimated and piece-picking can be realized.