Quentin Leboutet is an AI research scientist based in California with a strong robotics and ML foundation, blending 8+ years in academic and industrial R&D with five years of focused industry experience. He has driven generative and 3D foundation model advances at Intel—publishing in NeurIPS and TMLR—and now applies that expertise to research projects at Apple. Quentin’s background spans tactile sensing, state estimation, and control from his doctoral work at TUM, combined with hands-on prototyping skills from PCB and firmware design to multi-terrain robot integrations. He contributes to impactful open-source robotics efforts like OpenBot, bringing smartphone-based autonomy and embedded motor-control experience to low-cost robot platforms. That mix of high-impact publications, production-facing engineering, and hardware-software fluency gives him a rare ability to move ideas from lab to deployable systems.
5 years of coding experience
1 year of employment as a software developer
Master of Engineering (M.Eng.), Mechatronics, Robotics, and Automation Engineering, Master of Engineering (M.Eng.), Mechatronics, Robotics, and Automation Engineering at ENSEA
Master of Science (M.Sc.), Electrical Engineering and Information Technology, Master of Science (M.Sc.), Electrical Engineering and Information Technology at Technical University Munich
Doctor of Engineering (Dr. -Ing.), Robotics, Doctor of Engineering (Dr. -Ing.), Robotics at Technical University of Munich
OpenBot leverages smartphones as brains for low-cost robots. We have designed a small electric vehicle that costs about $50 and serves as a robot body. Our software stack for Android smartphones supports advanced robotics workloads such as person following and real-time autonomous navigation.
Role in this project:
Embedded Systems Engineer / IoT Developer & ML Engineer
Contributions:26 reviews, 12 commits, 3 PRs in 8 months
Contributions summary:Quentin contributed to the firmware and software aspects of the OpenBot project, primarily focusing on integrating new hardware components and features for various robot configurations, including the Multi-Terrain Vehicle (MTV) and OpenBot-Lite. Their work involved modifying the Arduino-based firmware, integrating sensor data, and configuring PWM signals for motor control. Furthermore, they integrated and refined a point goal navigation training pipeline, enhancing the robot's autonomous capabilities.
OpenBot leverages smartphones as brains for low-cost robots. We have designed a small electric vehicle that costs about $50 and serves as a robot body. Our software stack for Android smartphones supports advanced robotics workloads such as person following and real-time autonomous navigation.
Contributions:32 pushes, 2 branches in 1 year 2 months
serveslow-costrobotsnavigationreal-time
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