2022
A Hybrid Learning and Optimization Framework to Achieve Physically Interactive Tasks With Mobile Manipulators
Jianzhuang Zhao, Alberto Giammarino, Edoardo Lamon, Juan M. Gandarias, Elena De Momi, Arash Ajoudani
RA-L 2022
This letter proposes a hybrid learning and optimization framework for mobile manipulators for complex and physically interactive tasks. The framework exploits an admittance-type physical interface to obtain intuitive and simplified human demonstrations and Gaussian Mixture Model (GMM)/Gaussian Mixtu