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This project focuses on improving the accuracy of a large, cable-driven robot developed by the company Rbot9, called the Rocap. Unlike traditional robots with rigid arms, the Rocap uses multiple cables attached to a moving platform. By adjusting the length of each cable, the system can precisely position and orient the platform within a large workspace. Currently, the robot’s control system assumes that the weight it carries is constant and applied at a fixed point. In real-world situations, loads can change or shift position, causing small but important positioning errors. These errors reduce the robot’s performance in precision-demanding tasks. The goal of this project is to develop improved mathematical models and real-time compensation methods that allow the robot to automatically adjust to changing forces and loads. By better predicting and correcting positioning errors as they occur, the Rocap will achieve significantly higher accuracy. Enhancing the precision of this large-scale robotic system will enable its use in new industrial applications and support Rbot9’s expansion into growing markets that require reliable, high-accuracy automation solutions.
Philippe Cardou
Rbot9
Engineering
Manufacturing
Université Laval
Accelerate
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