Giuseppe L’Erario — accepted AI-conference papers

2024

Co-Design Optimisation of Morphing Topology and Control of Winged Drones

Fabio Bergonti, Gabriele Nava, Valentin Wüest, Antonello Paolino, Giuseppe L’Erario, Daniele Pucci +1

ICRA 2024poster

The design and control of winged aircraft and drones is an iterative process aimed at identifying a compromise of mission-specific costs and constraints. When agility is required, shape-shifting (morphing) drones represent an efficient solution. However, morphing drones require the addition of actua…

Cited by 14 Source ↗code ↗Scholar ↗

2024

From CAD to URDF: Co-Design of a Jet-Powered Humanoid Robot Including CAD Geometry

Punith Reddy Vanteddu, Gabriele Nava, Fabio Bergonti, Giuseppe L’Erario, Antonello Paolino, Daniele Pucci

IROS 2024poster

Co-design optimization strategies usually rely on simplified robot models extracted from CAD. While these models are useful for optimizing geometrical and inertial parameters for robot control, they might overlook important details essential for prototyping the optimized mechanical design. For insta…

Cited by 0 Source ↗Scholar ↗

2024

Learning to Walk and Fly with Adversarial Motion Priors

Giuseppe L’Erario, Drew Hanover, Ángel Romero, Yunlong Song, Gabriele Nava, Paolo Maria Viceconte +2

IROS 2024poster

Robot multimodal locomotion encompasses the ability to transition between walking and flying, representing a significant challenge in robotics. This work presents an approach that enables automatic smooth transitions between legged and aerial locomotion. Leveraging the concept of Adversarial Motion…

Cited by 1 Source ↗Scholar ↗