Giuliano Fabris

About

Giuliano Fabris is a researcher at the forefront of energy-efficient robotics and intelligent automation. His work centers on optimizing the dynamic performance of robotic systems—from parallel robots and linear axes to collaborative manipulators—by developing novel trajectory planning and control strategies that minimize both energy consumption and execution time. Fabris’s approach is distinguished by its focus on online optimization, enabling real-time adjustments for maximum efficiency in manufacturing environments. His most-cited paper, “Dynamic modelling and energy-efficiency optimization in a 3-DOF parallel robot” (21 citations), exemplifies this core contribution. Beyond industrial efficiency, Fabris explores the integration of artificial intelligence and collaborative robotics, as seen in his work on an intelligent checkers-playing system and a comprehensive survey on AI in the furniture industry. With multiple recent publications in 2024 and 2025, including experimental analyses of friction models, his research is rapidly gaining traction, offering practical solutions for sustainable, intelligent, and human-safe automation.

Research Focus

Key Achievements

Top Papers

1. 1
   Dynamic modelling and energy-efficiency optimization in a 3-DOF parallel robot

   21 citations · 2024
2. 2
   A survey on recent trends in robotics and artificial intelligence in the furniture industry

   10 citations · 2024
3. 3
   Playing Checkers with an Intelligent and Collaborative Robotic System

   7 citations · 2023
4. 4
   Experimental Analysis and Comparison of Friction Models Applied to the UR5e Robot

   7 citations · 2024
5. 5
   Online Optimization and Trajectory Planning for Energy Efficiency in a Robotic Linear Axis

   4 citations · 2024
6. 6
   Online optimization of minimum-time and minimum-energy trajectories for a 1-DOF belt-driven robotic system

   4 citations · 2025

Key Collaborators

Contact & Links