Glauco A. P. Caurin

About

Glauco A. P. Caurin is a Brazilian robotics researcher whose work spans intelligent autonomous systems, rehabilitation robotics, human-robot interaction, and engineering education. With a career bridging foundational robotics and cutting-edge machine learning applications, Caurin has made lasting contributions across remarkably diverse domains. His early work on robotic forklifts for intelligent warehouses (57 citations) demonstrated pioneering thinking in autonomous logistics systems, addressing path planning and localization challenges that remain central to modern industry. Simultaneously, his development of low-cost educational robots — the CellBot platform (44 citations) — reflects a sustained commitment to democratizing robotics education at the undergraduate level. Caurin has been particularly influential in rehabilitation robotics, pioneering adaptive serious game frameworks that use reinforcement learning and evolutionary algorithms to dynamically match game difficulty to patient performance, improving therapeutic engagement across multiple studies (37, 37, and 36 citations respectively). This body of work helped establish intelligent game-based rehabilitation as a credible research paradigm. More recently, his group's application of Vision Transformers to EMG-based hand motion classification (40 citations) signals a decisive move into deep learning for prosthetics and bionic interfaces. Across more than a decade of sustained output, Caurin's research consistently prioritizes human-centered technology — making him a significant voice in socially impactful robotics research.

Research Focus

Key Achievements

Top Papers

1. 1
   Robotic forklifts for intelligent warehouses: Routing, path planning, and auto-localization

   57 citations · 2010
2. 2
   Increasing Students' Interest With Low-Cost CellBots

   44 citations · 2012
3. 3
   Electromyography-Based, Robust Hand Motion Classification Employing Temporal Multi-Channel Vision Transformers

   40 citations · 2022
4. 4
   Dynamic Player Modelling in Serious Games Applied to Rehabilitation Robotics

   37 citations · 2014
5. 5
   Dynamic difficulty adjustment with Evolutionary Algorithm in games for rehabilitation robotics

   37 citations · 2016
6. 6
   Adaptive strategy for multi-user robotic rehabilitation games

   36 citations · 2011
7. 7
   Rehabilitation robotics and serious games: An initial architecture for simultaneous players

   34 citations · 2013
8. 8
   Kinect evaluation for human body movement analysis

   25 citations · 2012
9. 9
   The development of a robot terrain interaction system for walking machines

   20 citations · 2002
10. 10
    Online prediction of threading task failure using Convolutional Neural Networks

    17 citations · 2018

Key Collaborators

Contact & Links