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Vivian Suzano Medeiros

5 accepted papers

2026

Floating-Base Deep Lagrangian Networks

ICRA 2026poster

Grey-box methods for system identification combine deep learning with physics-informed constraints, capturing complex dependencies while improving out-of-distribution generalization. Despite the growing importance of floating-base systems such as humanoids and quadrupeds, current grey-box models ign…

2026

Load-Bearing Assessment for Safe Locomotion of Quadruped Robots on Collapsing Terrain

ICRA 2026poster

Collapsing terrains, often present in search and rescue missions or planetary exploration, pose significant challenges for quadruped robots. This paper introduces a robust locomotion framework for safe navigation over unstable surfaces by integrating terrain probing, load-bearing analysis, motion pl…

2025

Load-Bearing Assessment for Safe Locomotion of Quadruped Robots on Collapsing Terrain

RA-L 2025

Collapsing terrains, often present in search and rescue missions or planetary exploration, pose significant challenges for quadruped robots. This paper introduces a robust locomotion framework for safe navigation over unstable surfaces by integrating terrain probing, load-bearing analysis, motion pl

Cited by 0SourceScholar
2024

Introducing the Carpal-Claw: a Mechanism to Enhance High-Obstacle Negotiation for Quadruped Robots

ICRA 2024poster

The capability of a quadruped robot to negotiate obstacles is tightly connected to its leg workspace and joint torque limits. When facing terrain where the height of obstacles is close to the leg length, the locomotion robustness and safety are reduced since more dynamic motions are required to trav…

Cited by 2SourceScholar
2020

Trajectory Optimization for Wheeled-Legged Quadrupedal Robots Driving in Challenging Terrain

RA-L 2020

Wheeled-legged robots are an attractive solution for versatile locomotion in challenging terrain. They combine the speed and efficiency of wheels with the ability of legs to traverse challenging terrain. In this letter, we present a trajectory optimization formulation for wheeled-legged robots that

Cited by 90SourceScholar