7 papers
From Perception to Assistance: Open-Vocabulary Shared Autonomy for Robotic Manipulation
Murilo Vinicius da Silva, Ricardo V. Godoy, Juliano Negri +3
Teleoperating a robotic manipulator in industrial environments demands precision that camera-based interfaces alone struggle to deliver. The operator must align the end-effector wi…
Language-Guided Grasping under Partial Observation for Mobile Manipulation in Field Inspection and Maintenance
Dilermando Almeida, Juliano Negri, Guilherme Lazzarini +5
Offshore inspection and maintenance have increasingly been using legged robots for routine sensing, yet many useful interventions still require physical interaction with tools, con…
Optimizing Grasping in Legged Robots: A Deep Learning Approach to Loco-Manipulation
Dilermando Almeida, Guilherme Lazzarini, Juliano Negri +3
This paper presents a deep learning framework designed to enhance the grasping capabilities of quadrupeds equipped with arms, with a focus on improving precision and adaptability.…
A Vision-Based Shared-Control Teleoperation Scheme for Controlling the Robotic Arm of a Four-Legged Robot
Murilo Vinicius da Silva, Matheus Hipolito Carvalho, Juliano Negri +4
In hazardous and remote environments, robotic systems perform critical tasks demanding improved safety and efficiency. Among these, quadruped robots with manipulator arms offer mob…
Floating-Base Deep Lagrangian Networks
Lucas Schulze, Juliano Decico Negri, Victor Barasuol +4
Grey-box methods for system identification combine deep learning with physics-informed constraints, capturing complex dependencies while improving out-of-distribution generalizatio…
Autonomous UAV Flight Navigation in Confined Spaces: A Reinforcement Learning Approach
Marco S. Tayar, Lucas K. de Oliveira, Felipe Andrade G. Tommaselli +4
Autonomous UAV inspection of confined industrial infrastructure, such as ventilation ducts, demands robust navigation policies where collisions are unacceptable. While Deep Reinfor…