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Key Responsibilities
- Develop and implement model-based controllers (e.g., PID, whole-body control, MPC) for humanoid locomotion and manipulation.
- Design dynamic balance, gait generation, and disturbance recovery algorithms using analytical and optimization-based methods.
- Work with estimation engineers to fuse sensor data (IMU, joint encoders, force/torque sensors, vision) for state estimation and feedback control.
- Perform system identification and develop accurate dynamic models for control and simulation fidelity.
- Conduct experiments to evaluate control robustness, energy efficiency, and locomotion performance metrics.
Requirements
- Bachelor or higher in Mechanical Engineering, Robotics, Control Systems, or related field.
- Strong background in robot dynamics and control theory, including rigid-body dynamics, optimal control, and nonlinear systems.
- Proficiency in C++ and Python for real-time control and simulation.
- Hands-on experience with model-based controllers such as MPC, WBC, or impedance control.
- Familiarity with ROS / ROS 2, Eigen, and real-time middleware.
- Experience with dynamic simulation tools (e.g., Gazebo, PyBullet, MuJoCo, Drake, RaiSim).
Compensation:
- VinDynamics offers a competitive base, full benefits and other incentives. Flexible time-off policy. Focus on output and ability to work with an interdisciplinary team.
Location: Hanoi, Vietnam.
Job ID: 135906467