From the 1 of 8 linked papers with an AI index.
6 papers · 1 filter
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…
MIRA: A Modular Open-Source Micro-UAV for Indoor Research
Lucas K. de Oliveira, Felipe A. G. Tommaselli, João Aires Marsicano +5
MIRA is a low-cost, open-source micro-UAV with a modular 3D‑printed airframe and containerized software that enables low‑latency companion‑to‑autopilot communication for indoor rob…
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…
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…