Andreas Orthey
Principal Robotics Scientist at Realtime Robotics, Inc.
Berlin, Germany
Summary
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Rockstar🎓
Top SchoolAndreas Orthey is a Principal Robotics Scientist based in Berlin with 13 years of experience building high-performance robot motion planning systems for production environments. He blends deep academic training—a PhD in motion planning for humanoid robotics—with industry impact at Realtime Robotics, where he progressed from Staff to Principal Robotics Scientist. His expertise spans C++, optimization, and task planning, and he teaches motion planning as a guest lecturer at TU Berlin, bridging research and practice. Andreas is an active contributor to the well-known Open Motion Planning Library (OMPL), where he implemented a bridge-test sampler for narrow passages, demonstrating attention to both theory and robust backend engineering. Colleagues rely on him for turning advanced sampling and planning algorithms into reliable, production-ready code. He brings a researcher’s rigor and a pragmatist’s focus on performance and scalability to complex robotic systems.
13 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Motion Planning in Humanoid Robotics, Doctor of Philosophy (Ph.D.) Motion Planning in Humanoid Robotics at Toulouse INPMaster's Degree Computer Engineering, Master's Degree Computer Engineering at Technische Universität Berlin
German, French, English
Stackoverflow
101reputation
263reached
0answers
1question
Github Skills (10)
algorithm10
data-structures10
algorithms10
c-language10
robotics10
cprogramming-language10
motion-planning10
data-structure10
discrete-mathematics6
polyhedra6
Programming languages (5)
Github contributions (5)
ompl/ompl
Dec 2017 - Jan 2022
The Open Motion Planning Library (OMPL)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:33 reviews, 60 commits, 13 PRs in 4 years 2 months
Contributions summary:Andreas contributed significantly to the Open Motion Planning Library (OMPL), adding a new `BridgeTestValidStateSampler` class and its associated implementation files. This involved implementing a bridge test for sampling narrow passages using a probabilistic roadmap planner as described in a research paper. Further commits refined the implementation with bug fixes related to loop conditions, include guards, and license updates.
motion-planningomplrobotics
aorthey/ompl
Dec 2017 - Apr 2026
The Open Motion Planning Library (OMPL), mirror of:
Contributions:11 PRs, 361 pushes, 26 branches in 8 years 5 months
motion-planningompl
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