1 code implementation • 4 Mar 2021 • Giovanni Franzese, Anna Mészáros, Luka Peternel, Jens Kober
Teaching robots how to apply forces according to our preferences is still an open challenge that has to be tackled from multiple engineering perspectives.
1 code implementation • 9 Oct 2021 • Anna Mészáros, Giovanni Franzese, Jens Kober
This work investigates how the intricate task of a continuous pick & place (P&P) motion may be learned from humans based on demonstrations and corrections.
1 code implementation • 2 Sep 2023 • Lucas Cosier, Rares Iordan, Sicelukwanda Zwane, Giovanni Franzese, James T. Wilson, Marc Peter Deisenroth, Alexander Terenin, Yasemin Bekiroglu
To control how a robot moves, motion planning algorithms must compute paths in high-dimensional state spaces while accounting for physical constraints related to motors and joints, generating smooth and stable motions, avoiding obstacles, and preventing collisions.
1 code implementation • 13 Dec 2021 • Cristian Meo, Giovanni Franzese, Corrado Pezzato, Max Spahn, Pablo Lanillos
Adaptation to external and internal changes is major for robotic systems in uncertain environments.