Giuseppe Rizzi — accepted AI-conference papers

2023

Learning Agent-Aware Affordances for Closed-Loop Interaction with Articulated Objects

Giulio Schiavi, Paula Wulkop, Giuseppe Rizzi, Lionel Ott, Roland Siegwart, Jen Jen Chung

ICRA 2023poster

Interactions with articulated objects are a challenging but important task for mobile robots. To tackle this challenge, we propose a novel closed-loop control pipeline, which integrates manipulation priors from affordance estimation with sampling-based whole-body control. We introduce the concept of…

Cited by 22 Source ↗code ↗Scholar ↗

2022

A Planning-and-Control Framework for Aerial Manipulation of Articulated Objects

Maximilian Brunner, Giuseppe Rizzi, Matthias Studiger, Roland Siegwart, Marco Tognon

RA-L 2022

While the variety of applications for Aerial Manipulators (AMs) has increased over the last years, they are mostly limited to push-and-slide tasks. More complex manipulations of dynamic environments are poorly addressed and still require handcrafted designs of hardware, control, and trajectory plann

Cited by 45 Source ↗Scholar ↗