ko-br provides automated palletizing solutions engineered to handle mixed SKU environments efficiently. Their system adapts in real-time to varying pallet configurations and conveyor positions, offering flexible throughput up to 15 picks per minute. The company offers flexible rental or purchase options backed by a 90-day KPI-guaranteed pilot program.
Funding
Funding not disclosed
Founders
Product
Problem
Warehouses and fulfillment centers face challenges in automating palletizing and depalletizing tasks due to the variability in SKU sizes, shapes, and orientations. Traditional robotic solutions require extensive programming and struggle to adapt to unstructured environments, leading to frequent emergency stops and costly manual intervention. This inflexibility results in significant financial losses and limits the potential for widespread automation in logistics.
Solution
ko-br provides an AI-powered vision system that enables robotic arms to automate palletizing and depalletizing tasks in chaotic environments. The system uses computer vision and imitation learning to allow robots to learn from human demonstrations, eliminating the need for complex coding. The AI adapts to mixed SKUs, recovers from grip slips and jams, and handles variations in lighting and dust conditions. This self-healing autonomy reduces emergency stops and protects margins for system integrators and warehouse operators.
Target Audience
The primary target audience includes system integrators who deploy robotic solutions in warehouses and fulfillment centers, as well as warehouse operators seeking to automate palletizing and depalletizing processes.
Features
- Vision-guided system for robotic arms that automates palletizing and depalletizing of mixed SKUs
- AI-powered system trained via human demonstrations, eliminating the need for coding
- Self-healing protocols enable robots to autonomously recover from grip slips and jams
- Real-world trained vision handles dust and lighting changes in warehouse environments
- OEM-agnostic control allows for plug-and-play deployment across ABB, KUKA, and UR robots
- LED projections and camera systems for no-code visual guidance
- Data Dignity framework compensates workers for training robots