Christoph Roesmann
Staff AI ML Research Engineer at Apple
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolChristoph Roesmann is a Staff AI/ML Research Engineer and control theorist with 11 years of experience building real-world robotics and intelligent systems, currently leading technical efforts in Apple's Special Projects Group in the San Francisco Bay Area. He combines deep academic training (Dr.-Ing. in Control Theory) with hands-on expertise in nonlinear model predictive control, time-optimal planning, and sparse optimization to deliver robust trajectory planning for mobile and car-like robots. At TU Dortmund he drove open-source C++ toolchains for MPC and contributed improvements to the teb_local_planner ROS package, enhancing dynamic obstacle avoidance and H-signature computations. Known for bridging research and production, he has supervised dozens of theses and translated algorithms into patented industrial solutions and shipped R&D at scale. His work blends theoretical rigor with system-level pragmatism—optimizing control formulations while hardening software for edge robotics deployments. Colleagues rely on him for tough algorithmic problems that must also run reliably on real hardware.
11 years of coding experience
10 years of employment as a software developer
Doctor of Engineering (Dr.-Ing.) Control Theory - Electrical Engineering and Information Technology, Doctor of Engineering (Dr.-Ing.) Control Theory - Electrical Engineering and Information Technology at TU Dortmund University
Github Skills (10)
trajectory-optimization10
pathfinding10
c-language10
cprogramming-language10
obs10
ros10
algorithms8
data-structures8
algorithm8
data-structure8
Programming languages (4)
Github contributions (5)
rst-tu-dortmund/teb_local_planner
May 2015 - Jul 2020
An optimal trajectory planner considering distinctive topologies for mobile robots based on Timed-Elastic-Bands (ROS Package)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:1 release, 442 commits, 64 PRs in 5 years 2 months
Contributions summary:Christoph's contributions primarily involve modifying and extending the `teb_local_planner` project, a ROS package for mobile robot navigation. They implemented changes to improve the accuracy and performance of obstacle avoidance algorithms, specifically for dynamic obstacles. The code modifications include enhancing the computation of the H-Signature, which is central to the planner's approach to trajectory optimization and path selection. Furthermore, the user has improved the handling of the trajectory, ensuring better robustness in cases where the robot may be close to the goal.
path-planningroboticsmobile-robotsros-packageelastic
rst-tu-dortmund/teb_local_planner_tutorials-release
Apr 2016 - Jul 2019
Contributions:130 pushes, 76 branches, 6 tags in 3 years 3 months
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