Machine learning based interaction force prediction in multi-disk continuum robot arms for human-robot collaboration

Abstract Accurate prediction of interaction forces in robotic manipulators is critical for safe human-robot collaboration and precise manipulation. Multi-disk continuum robot arms present unique modelling challenges owing to high degrees of freedom, complex mechanical coupling, and non-linear force transmission. This study presents a investigation of eight regression algorithms Linear Regression, Ridge, Lasso, Decision Tree, Random Forest, Gradient Boosting, XGBoost, and Support Vector Regressio