Maxim Vochten

Department of Mechanics,

Avenue De La Renaissance 30,

1000 Brussels, Belgium.

About

I am a Senior Researcher within the Robotics & Autonomous Systems unit at the Royal Military Academy (RMA), Belgium.

I lead the team at RMA within the European Defense Funds project GENIUS on robotic demining.

Robot demining

In the GENIUS project on robotic demining, we research robotic technologies that can improve the speed and safety of detecting and disposing of land mines.

Invariant trajectory representations

From 2018-2024, I was mainly active on the Robotgenskill project which focuses on the generalization of human-demonstrated robot skills. The main aim was to develop techniques to learn data-efficient task representations from sparse human demonstrations by exploiting coordinate-invariant properties in the recorded trajectory data. The resulting coordinate-invariant models can be used for human intent recognition, as well as trajectory generation on the robot from the invariant motion template.

PhD supervision

Within the context of the Robotgenskill project, I was the co-promotor of two PhD candidates:

Arno Verduyn (2020-2025): Analysis, recognition and generalization of human-demonstrated skills using invariant trajectory representations. KU Leuven.
Riccardo Burlizzi (2021-2025): Data augmentation in robot learning from demonstration using invariant trajectory representations. KU Leuven.

Master thesis supervision

During my PhD and PostDoc at KU Leuven, I have mentored and co-supervised over 15 master thesis students in the Master of Mechanical Engineering programme (and the Master of Artificial Intelligence programme).

Software

For my research on invariant trajectory descriptors, I am developing software packages in Matlab and Python: invariants_mat and invariants_py. These packages support the robust numerical calculation of invariant descriptors and also support the generation of trajectories in an invariant way. A corresponding documentation website is being developed: Trajectory Invariants.

In my research I frequently make use of the following specialized software libraries for robotics:

eTaSL for task specification and reactive sensor-based control
CasADi for solving optimal control problems and nonlinear optimization problems
ROS for building robotics applications integrating sensing, motion generation, control, and visualization
Orocos for building fast robot controllers

News

Jan 17, 2025	I’m happy to share that I’m starting a new position as Senior Researcher at the Royal Military Academy (RMA) as part of the Robotics & Autonomous Systems unit in the Department of Mechanics. I will lead the team at RMA within the European Defense Funds project GENIUS on robotic demining. My research activities will involve developing robotic technologies for the perception and safe disposal of mines.
Apr 18, 2024	At the upcoming ICRA 2024 conference in Yokohama I will present our work on invariant trajectory descriptors and Arno will present our work on self-supervised trajectory segmentation. Presentations are on Wednesday 15th of May.
Jan 19, 2024	Our paper on self-supervised trajectory segmentation has been accepted for the ICRA 2024 conference in Yokohama, Japan!
Dec 20, 2023	Our paper on interpreting contact tasks using coordinate-invariant trajectory representations has been published in the December 2023 issue of the IEEE Transactions on Robotics.
Aug 21, 2023	Arno Verduyn will present our paper on trajectory generation for robotic spray painting at the upcoming IEEE CASE conference in Auckland, New Zealand, on 28 August 2023.

Selected publications

TRO

Invariant Descriptors of Motion and Force Trajectories for Interpreting Object Manipulation Tasks in Contact

Maxim Vochten, Ali Mousavi Mohammadi, Arno Verduyn, Tinne De Laet, Erwin Aertbeliën, and Joris De Schutter

IEEE Transactions on Robotics, 2023

Bib HTML PDF

@article{vochten2023invariant,
  author = {Vochten, Maxim and Mohammadi, Ali Mousavi and Verduyn, Arno and De Laet, Tinne and Aertbeliën, Erwin and De Schutter, Joris},
  journal = {IEEE Transactions on Robotics},
  title = {Invariant Descriptors of Motion and Force Trajectories for Interpreting Object Manipulation Tasks in Contact},
  year = {2023},
  volume = {39},
  number = {6},
  pages = {1-21},
  issn = {1941-0468},
  publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
  url = {http://dx.doi.org/10.1109/TRO.2023.3309230},
  doi = {10.1109/TRO.2023.3309230},
}

ICRA

Enhancing motion trajectory segmentation of rigid bodies using a novel screw-based trajectory-shape representation

Arno Verduyn, Maxim Vochten, and Joris De Schutter

In 2024 IEEE International Conference on Robotics and Automation (ICRA) , 2024

Bib PDF

@inproceedings{verduyn2024enhancing,
  title = {Enhancing motion trajectory segmentation of rigid bodies using a novel screw-based trajectory-shape representation},
  author = {Verduyn, Arno and Vochten, Maxim and De Schutter, Joris},
  booktitle = {2024 IEEE International Conference on Robotics and Automation (ICRA)},
  pages = {7179--7185},
  year = {2024},
  organization = {IEEE},
  doi = {10.1109/ICRA57147.2024.10610030},
}