Autonomous self-calibration of cable-driven parallel robots

Brief Project Description

This project deals with machine learning algorithms for the autonomous calibration of a large-scale robot by only using internal sensors (no external ground truth). The project will require to implement conventional methodologies (based on recursive least squares and direct robot pose measurements) and compare them with the project results in terms of robot tracking accuracy and pose repeatability.

This thesis is conducted in collaboration with: DIN UNIBO

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