Max Spahn Ph.D.
Freiburg, Germany
About
Driven by a passion for developing innovative software solutions for robotic applications, my career has focused on creating efficient algorithms for motion planning and control. Over the past six years in both academic and corporate research, I have contributed to the research in new methods, and implemented several existing solutions known from the academic world to get them closer to the business application.
My time in cooperative research projects has given me the opportunity to work with business partners that put a strong focus on reliability and added value for the customer. My next goal is to bring my expertise in robotics to the medical sector, as it promises the biggest impact on society and robotics applications are still in the early stages.
Skills
programming: Python, C++, git, ROS1/ROS2, LaTeX, bash, Azure DevOps, GTest
optimization: non-linear constrained optimization for dynamic programming, optimization on Riemannian manifolds, Bayesian optimization for hyperparameter tuning
robotics: forward and inverse kinematics, impedance control for compliant trajectory generation, receding horizon motion control, collision avoidance in human-shared environments in real-time
project management: leading and contributing to collaborative research projects, leading cooperate research projects with stakeholders from multiple business lines
languages: German, English and French
Experience
2025-
Research Scientist at ABB AG
- Researching new technologies for motion planning and control for industrial robots
- Integration of product-relevant features into software stacks for industrial robots
- Project lead for the development of mobile manipulation solutions for lab automation
2024
Post-Doctoral Researcher @ Delft University of Technology
- Integrating non-Riemannian trajectory generation into manipulation tasks
- Leading a group of researchers to develop a live demo of
multiple mobile manipulators in a human-shared environment
Education
2020-2024
Ph.D. in Robotics @ Delft University of Technology
- Thesis: Trajectory Generation for Mobile Manipulators with Differential Geometry (Defense: 11.12.2024)
- Reactive trajectory generation for high-dimensional robots
- Using the geometry of the robot’s configuration space to generate consistent
- Combining several research projects into a proof-of-concept demonstration in supermarket automation
2013-2019
RWTH Aachen, Mechanical Engineering, B.Sc. and M.Sc.
- focus on computational fluid dynamics and robotics
- Master thesis: Modeling High Weissenberg number flows in OpenFOAM
- Bachelor thesis: A Robust and Predictable Algorithm for the Numerical Solution of the Inverse Kinematics Problem for Serial Robots
2015-2017
École Centrale Supéléc Paris, M.Sc. (Double Degree T.I.M.E.)
- focus on fundamental mathematics
- several courses on algorithms and computer science
Publications
Journals
2025
M Spahn, S Bakker, J Alonso-Mora: “Overcoming Explicit Environment Representations with Geometric Fabrics”, IEEE Robotics and Automation Letters
2025
T Merva, S Bakker, M Spahn, D Zhao, I Virgala, J Alonso-Mora: “Globally-Guided Geometric Fabrics for Reactive Mobile Manipulation in Dynamic Environments”, IEEE Robotics and Automation Letters
2025
C Pezzato, C Salmi, E Trevisan, M Spahn, J Alonso-Mora, CH Corbato: “Sampling-based Model Predictive Control Leveraging Parallelizable Physics Simulations”, IEEE Robotics and Automation Letters
2023
M. Spahn, M. Wisse, J. Alonso-Mora: “Dynamic Optimization Fabrics for Motion Generation”, IEEE Transactions on Robotics
2022
C. Meo, G. Franzese, C. Pezzato, M. Spahn, P. Lanillos: “Adaptation Through Prediction: Multisensory Active Inference Torque Control”, IEEE Transactions on Cognitive and Developmental Systems
2020
M. Frings, N. Hosters, C. Müller, M. Spahn, C. Susen, K. Key, S. Elgeti: SplinLib: A Modern Multipurpose C++ Spline Library”, Advances in Engineering Software
Conferences
2024
M. Spahn, C. Pezzato, C. Salmi, R. Dekker, C. Wang, C. Pek, J. Kober, J. Alonso-Mora, C. Hernandez Corbato, M. Wisse: “Demonstrating Adaptive Mobile Manipulation in Retail Environments”, Robotics: Science and Systems
2023
M. Spahn, J. Alonso-Mora: “Autotuning Symbolic Optimization Fabrics for Trajectory Generation”, IEEE International Conference on Robotics and Automation
2023
S. Bakker, L. Knödler, M. Spahn, W. Böhmer, J. Alonso-Mora: “Multi-Robot Local Motion Planning Using Dynamic Optimization Fabrics”, IEEE International Symposium on Multi-Robot & Multi-Agent Systems
2022
M. Spahn, C. Salmi, J. Alonso-Mora: “Local Planner Bench: Benchmarking for Local Motion Planning”, Workshop at IEEE/RSJ International Conference on Intelligent Robots and Systems
2021
M. Spahn, B. Brito, J. Alonso-Mora: “Coupled Mobile Manipulation via Trajectory Optimization with Free Space Decomposition”, IEEE International Conference on Robotics and Automation
Projects
Geometric Fabrics for robot trajectory generation
- Geometric fabrics formulate trajectory generation as second order dynamical systems on (non-)Riemannian manifolds
- This implementation is robot-agnostic and has been used in several research projects
- The project uses continuous integration and modern software engineering practices
- https://github.com/tud-amr/fabrics
Generic robotics gymnasium wrapper for pybullet and MuJoCo
- generic robotics gymnasium wrapper for pybullet and MuJoCo
- the wrapper is used by several researchers and students
- https://github.com/maxspahn/gym_envs_urdf
Robothon 2023, Platonics Delft
- participated in the Robothon 2023 with the Platonics Delft Team
- completed all manipulation tasks using learning-from-demonstration
- https://platonics-delft.github.io
Interests
- learning from my child, running, football, vegan cooking