Luciane Baldassari

University of Rio Grande and Rio Grande Community College, Universidade Federal do Rio Grande

Papers

Total Citations

H-Index

About

Luciane Baldassari’s research lies at the intersection of human-robot interaction, industrial automation, and welding process optimization. Her work focuses on making robotic welding systems more intuitive and safer for human operators, particularly by developing vision-based perception and semiotic communication interfaces. In her most cited paper, “Perception of an Opto-Mechanical Torch for Linear Welding Robot Using Monocular Camera” (2018, 5 citations), she introduced a monocular camera system that enables a welding robot to autonomously perceive and correct its torch position, reducing the operator’s exposure to hazardous fumes, sparks, and radiation. This contribution directly addresses the challenge of transitioning from manual welding to semi-automated robotic systems. Her follow-up work, “Semiotics Applied to Human-Robot Interaction in Welding Processes” (2019, 2 citations), pioneered the use of semiotic theory to design clearer, more efficient teleoperation interfaces for welding robots, improving operator decision-making and reducing cognitive load. Though her citation counts are modest, Baldassari’s research is notable for its interdisciplinary approach—merging robotics, computer vision, and semiotics—to solve practical safety and usability problems in manufacturing. Her work offers valuable insights for engineers and researchers developing human-centered automation in hazardous industrial environments.