Thiago Eustaquio Alves de Oliveira

About

Thiago Eustaquio Alves de Oliveira is a robotics researcher whose work sits at the intersection of tactile sensing, machine learning, and dexterous robotic manipulation. With a career dedicated to bridging the gap between human and robotic touch, his research has made significant contributions to how robots perceive, identify, and interact with objects in unstructured environments. His pioneering work on bio-inspired multimodal tactile sensing modules — among his most influential publications, garnering over 60 citations — has advanced the field's understanding of how robots can simultaneously capture surface geometry, forces, and vibrations in ways that mimic biological touch. His investigations into texture classification, object recognition during grasping, and in-hand object orientation estimation using machine learning demonstrate a consistent drive to make robotic hands genuinely capable of human-like dexterity. Beyond sensing, Oliveira has expanded into human-robot interaction, including sign language recognition and haptic-feedback teleoperation systems. His cumulative body of work, exceeding 240 citations across ten highly regarded publications, reflects a researcher steadily shaping the future of intelligent robotic hands and their real-world deployment in healthcare, manufacturing, and hazardous environments.

Research Focus

Key Achievements

Top Papers

1. 1
   Multimodal Bio-Inspired Tactile Sensing Module

   61 citations · 2017
2. 2
   Multimodal Bio-Inspired Tactile Sensing Module for Surface Characterization

   35 citations · 2017
3. 3
   Touch sensing for humanoid robots

   27 citations · 2015
4. 4
   Estimating the Orientation of Objects from Tactile Sensing Data Using Machine Learning Methods and Visual Frames of Reference

   26 citations · 2019
5. 5
   Tactile object recognition in early phases of grasping using underactuated robotic hands

   22 citations · 2022
6. 6
   Teaching a Robot Sign Language using Vision-Based Hand Gesture Recognition

   18 citations · 2018
7. 7
   Computational intelligence and mechatronics solutions for robotic tactile object recognition

   18 citations · 2015
8. 8
   Teleoperated Grasping Using a Robotic Hand and a Haptic-Feedback Data Glove

   13 citations · 2020
9. 9
   Classification of Textures using a Tactile-Enabled Finger in Dynamic Exploration Tasks

   11 citations · 2021
10. 10
    A multimodal tactile dataset for dynamic texture classification

    11 citations · 2023

Key Collaborators

Contact & Links