Steve Vanlanduit

About

Steve Vanlanduit is a prominent researcher whose work sits at the intersection of robotics, human-robot interaction (HRI), and computer vision. His research portfolio reflects a deep commitment to making robotic systems safer, smarter, and more intuitive for human collaboration. Among his most influential contributions is the development of the CoppeliaSim VR Toolbox, which bridges robot simulation with virtual reality to enable rapid prototyping and verification of robotic systems, garnering 35 citations. Equally impactful is his GazeEMD framework, also with 35 citations, which advances gaze-based HRI by accurately detecting human visual intention, allowing robotic manipulators to respond to natural eye movements. Vanlanduit has made notable strides in robot safety, proposing Bayesian deep neural networks for collision avoidance during HRI and developing deep regression models for safety-aware visual servoing. His contributions to inspection path optimization and fractional-order controller auto-tuning further demonstrate his versatility across both theoretical and applied robotics. His work on gaze gesture recognition using graph convolutional networks highlights his engagement with cutting-edge machine learning techniques. Collectively, his publications have accumulated well over 170 citations, establishing him as a significant voice in intelligent, human-centered robotics research.

Research Focus

Key Achievements

Top Papers

1. 1
   Connecting the CoppeliaSim robotics simulator to virtual reality

   35 citations · 2020
2. 2
   GazeEMD: Detecting Visual Intention in Gaze-Based Human-Robot Interaction

   35 citations · 2021
3. 3
   A Gradient-Based Inspection Path Optimization Approach

   22 citations · 2018
4. 4
   A Bayesian Deep Neural Network for Safe Visual Servoing in Human–Robot Interaction

   18 citations · 2021
5. 5
   Calibration of UR10 Robot Controller through Simple Auto-Tuning Approach

   17 citations · 2018
6. 6
   Gaze Gesture Recognition by Graph Convolutional Networks

   14 citations · 2021
7. 7
   Experimental Validation of a Novel Auto-Tuning Method for a Fractional Order PI Controller on an UR10 Robot

   13 citations · 2018
8. 8
   Application of Visual Servoing and Eye Tracking Glass in Human Robot Interaction: A case study

   6 citations · 2019
9. 9
   Comparison of Deep Learning Models in Position Based Visual Servoing

   6 citations · 2022
10. 10
    A Deep Regression Model for Safety Control in Visual Servoing Applications

    4 citations · 2020

Key Collaborators

Contact & Links