Lead the development and integration of motion control capabilities for our robots.
The successful candidate will be responsible for enabling robust full-body motion, balance, locomotion, and safe interaction on a mechanically challenging humanoid platform with constrained actuators, significant gearbox backlash, friction, limited sensing, and limited computing and energy resources.
As the main motion control expert within the team, the engineer will work with a high level of autonomy, define the technical roadmap, propose pragmatic solutions, and guide less-experienced motion engineers, including engineers based overseas.
Key Responsibilities
Motion Control Development
- Design, implement, and optimize full-body motion control algorithms for balance, locomotion, posture control, coordinated motion, disturbance rejection, and safe motion transitions.
- Evaluate and select the most appropriate methods for each application, including classical feedback control, model-based control, trajectory optimization, whole-body control, impedance control, learning-based control, or hybrid approaches.
- Adapt control strategies to the real characteristics and limitations of the robot, including friction, backlash, actuator saturation, sensor limitations, structural compliance, and communication latency.
- Translate product use cases into measurable motion performance requirements.
- Design and implement a real-time safety architecture covering fall detection, fault detection, safe-state management, and recovery.
Exploration of Advanced Control Approaches
- Explore the applicability of Reinforcement Learning, impedance control, and other modern control techniques to NAO7.
- Design experiments to determine whether these approaches provide meaningful benefits on the physical platform.
- Develop simulation, domain randomization, and sim-to-real methodologies when relevant.
- Maintain a critical and pragmatic approach: advanced methods should be adopted only when their performance, robustness, and product value are demonstrated.
- Combine conventional and learning-based methods when a hybrid approach offers the best trade-off.
Simulation, Integration and Validation
- Develop and maintain kinematic, dynamic, actuator, friction, backlash, and contact models.
- Use simulation environments such as MuJoCo, Isaac Sim, Gazebo, or equivalent tools to develop and validate motion algorithms.
- Integrate motion control software into the real-time robotic platform.
- Define control-loop timing, software interfaces, data flows, diagnostics, and safety mechanisms.
- Establish repeatable testing, performance metrics, regression tests, and simulation-to-real validation processes.
- Diagnose motion issues using logging, replay, monitoring, and experimental characterization.
- Validate the system through simulation and fault-injection tests to ensure predictable and safe behavior in all operating conditions
Technical Leadership
- Act as the technical owner and main reference for motion control topics.
- Define development priorities and identify technical risks and platform limitations.
- Work closely with mechanical, electronics, embedded software, simulation, AI, and product teams.
- Guide and mentor junior motion engineers, particularly within distributed international teams.
- Review technical proposals, algorithms, models, software, and experimental results.
- Establish clear engineering practices and documentation for motion development.
Required Experience and Skills
- Strong experience in humanoid robotics, legged robotics, motion control, or a closely related field.
- Proven experience deploying control algorithms on physical robotic systems.
- Strong knowledge of robot kinematics and dynamics, feedback control, state estimation, trajectory generation, balance, locomotion, and contact control.
- Ability to work across classical, model-based, optimization-based, and learning-based control approaches.
- Strong proficiency in C++ and Python.
- Experience with real-time systems and robotic simulation environments.
- Strong experimental and system-level engineering mindset.
- Ability to work autonomously, structure an emerging technical activity, and make pragmatic decisions with incomplete information.
- Strong communication skills in English.
Preferred Qualifications
- Master’s degree or PhD in robotics, control engineering, mechatronics, or a related field.
- Experience with humanoid robots or mechanically constrained robotic platforms.
- Experience with gearbox friction, backlash, limited actuator bandwidth, and systems without direct joint torque sensing.
- Experience with whole-body control, model predictive control, inverse dynamics, impedance control, Reinforcement Learning, or sim-to-real transfer.
- Experience mentoring engineers or leading technical activities across international teams.
Experience Level
Typically 7+ years of relevant experience, or equivalent demonstrated expertise in deploying advanced motion control on real robots.