Print Email Facebook Twitter Improving model-based control of a soft robot via gaussian process regression Title Improving model-based control of a soft robot via gaussian process regression Author Tavio Y Cabrera, Emilio (TU Delft Mechanical, Maritime and Materials Engineering) Contributor Della Santina, C. (mentor) Borja Rosales, Pablo (mentor) Babuska, R. (graduation committee) Degree granting institution Delft University of Technology Programme Mechanical Engineering | Vehicle Engineering Date 2023-03-15 Abstract Soft robots have the potential to accelerate robotiza- tion in areas that are complex and impractical for hard robots. The use of soft materials results in a safe and flexible design that is unattainable for hard robots. However, this attribute results in the need for new control approaches and strategies. Hybrid controllers are a relative unexplored type of controllers that consist of a model-based controller part and a learning part to correct the model-based controller. A hybrid controller benefit by the unrequired need for accurate system identification. Simultaneously, the learning effort is reduced by the preliminary work of the model-based component. In this project, a model-based feedforward controller is pro- posed and compared with a hybrid controller consisting of the same model-based controller enhanced with a Gaussian process to reduce the end-point error in the bending angle. The controllers are tested using a crafted 2-segment pneumatic silicone soft robot, following a circular trajectory with different radii. The results of this new control strategy highlights the poten- tial benefits of adding a learning approach to a model-based controller to reduce model errors. Using a relative small dataset preserves a computational usable Gaussian process. The small dataset remains effective by reducing the range of the training data. Subject soft robotGaussian Process RegressionHybrid control To reference this document use: http://resolver.tudelft.nl/uuid:9550e2de-c580-4de0-b59b-ca777147eda6 Part of collection Student theses Document type master thesis Rights © 2023 Emilio Tavio Y Cabrera Files PDF Improving_Model_Based_Con ... _cover.pdf 3.69 MB Close viewer /islandora/object/uuid:9550e2de-c580-4de0-b59b-ca777147eda6/datastream/OBJ/view