Our Projects
Using AI and Robotics for more profitable businesses.
No matter their challenge, our clients benefit from our end-to-end AI and Robotics solutions tailored to their needs. From building AI inspection models to robotizing factory processes, we create best-in-class technologies and guide our clients every step of the way.
Discover how we helped our clients with tailored AI and Robotics solutions!
Developing a custom voltage sensor to measure battery voltage in real time
The manual measurement of stored batteries for quality assurance was a costly and labor-intensive process for Landport Batteries. Cboost was asked to robotize this process, but we identified a more efficient solution. We developed the Landport Voltage Sensor (LVS) which enhanced quality assurance for Landport’s customers while reducing maintenance costs.
Technologies used:
![Beeld-bij-Landport-720x540](https://cboost.nl/wp-content/uploads/2024/05/Beeld-bij-Landport-720x540-2-768x576.jpeg)
![Landport Louwman Cboost solution](https://cboost.nl/wp-content/uploads/2024/05/Screenshot-2024-05-02-at-10.10.42-1-768x576.png)
Developing an AI model to increase picking accuracy and item range of Pick & Place robots
Smart Robotics is a Pick & Place partner providing unique technology and services to automate pick and place stations. With their Smart Item Picker, they experienced challenges related to reflection and refraction. Through an AI-powered Computer Vision Model, Cboost increased picking accuracy from 75% to 99.86%, while also increasing throughput for hard-to-pick items by 50% and the robot’s item range.
Technologies used:
![Picture1](https://cboost.nl/wp-content/uploads/2023/06/Picture1-768x543.png)
![Screenshot 2024-03-01 at 15.49.07](https://cboost.nl/wp-content/uploads/2024/03/Screenshot-2024-03-01-at-15.49.07-e1709304698311-768x544.png)
Improving human-machine interaction for street construction robot
Smart Robotics is a Pick & Place partner providing unique technology and services to automate pick and place stations. With their Smart Item Picker, they experienced challenges related to reflection and refraction. Through an AI-powered Computer Vision Model, Cboost increased picking accuracy from 75% to 99.86%, while also increasing throughput for hard-to-pick items by 50% and the robot’s item range.
Technologies used:
![Screenshot_2024-05-03_at_11.57.32-removebg-preview (1)](https://cboost.nl/wp-content/uploads/2024/06/Screenshot_2024-05-03_at_11.57.32-removebg-preview-1-1.png)
![Street Robotics Cboost solution](https://cboost.nl/wp-content/uploads/2024/06/Screenshot-2024-03-21-at-16.28.22-1.png)