Olivier Gibaru

About

Olivier Gibaru is a prominent researcher whose work spans industrial robotics, human-robot collaboration, and machine learning applications in automation. Based at the intersection of precision engineering and intelligent systems, he has made substantial contributions to advancing the capabilities and accessibility of industrial and collaborative robots. Gibaru's early foundational work focused on improving robot performance in manufacturing contexts, with his research on feedrate planning for six-axis robots (105 citations) and offline joint error compensation (70 citations) addressing critical limitations in robot accuracy that had long restricted their use in precision machining and prototyping. His trajectory planning research further refined robot motion efficiency in industrial settings. As the field evolved, Gibaru extended his expertise into human-robot interaction, pioneering gesture-based robot control using neural networks and developing online recognition systems for incomplete gesture data (52 citations), making collaborative robots more intuitive and accessible. His application of CNN features to unsupervised classification (70 citations) demonstrated a notable versatility into deep learning research. Perhaps most impactful is his sustained work on collaborative robotics safety — through comprehensive surveys and design methodologies (58 and 51 citations respectively) — directly tackling the barriers slowing industrial adoption of collaborative systems. His 3D metrology and ergonomic assembly optimization research further illustrates a career dedicated to bridging theoretical robotics with real-world industrial benefit.

Research Focus

Key Achievements

Top Papers

1. 1
   Feedrate planning for machining with industrial six-axis robots

   105 citations · 2010
2. 2
   Improving the accuracy of industrial robots by offline compensation of joints errors

   70 citations · 2012
3. 3
   CNN features are also great at unsupervised classification

   70 citations · 2017
4. 4
   Survey of methods for design of collaborative robotics applications- Why safety is a barrier to more widespread robotics uptake

   58 citations · 2018
5. 5
   Online Recognition of Incomplete Gesture Data to Interface Collaborative Robots

   52 citations · 2019
6. 6
   Methods for considering safety in design of robotics applications featuring human-robot collaboration

   51 citations · 2020
7. 7
   3D Metrology Using a Collaborative Robot with a Laser Triangulation Sensor

   30 citations · 2017
8. 8
   Enhanced trajectory planning for machining with industrial six-axis robots

   24 citations · 2010
9. 9
   Natural control of an industrial robot using hand gesture recognition with neural networks

   24 citations · 2016
10. 10
    Economic and ergonomic performance enhancement in assembly process through multiple collaboration modes between human and robot

    22 citations · 2022

Key Collaborators

Contact & Links