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About the role
As a Control Engineer, you will play a vital role in supporting the deployment of stable and robust control on legged robotic platforms. Your primary responsibilities will include: - Designing, analyzing, and implementing control algorithms for legged locomotion systems. - Designing and deploying Model Predictive Controllers (MPC) for balancing and trajectory tracking. - Developing and tuning classical controllers such as PID, lead-lag, state-space, and observer-based controllers. - Analyzing system stability using Nyquist plots, Bode plots, root locus, Lyapunov stability, and frequency-domain methods. - Modeling and controlling nonlinear dynamic systems including inverted pendulum and double inverted pendulum systems. - Working on dynamic balancing, disturbance rejection, contact stability, and whole-body control concepts. - Validating controllers through simulation and real-world robotic deployment. To qualify for this role, you should have the following qualifications: - Minimum Masters degree in Robotics, Control Systems, Mechanical Engineering, Electrical Engineering, or a related field. - Strong background in Control Theory, Dynamics, and Robotics. - Experience with stability analysis and classical control methodologies. - Hands-on experience with MPC deployment in real-time systems. - Familiarity with legged robot dynamics and locomotion principles. - Proficiency in MATLAB/Simulink, Python, or C++. - Understanding of nonlinear systems and trajectory optimization is preferred. Additionally, the following experience would be preferred: - Experience with humanoids, quadrupeds, or double inverted pendulums systems. - Knowledge of ROS/ROS2 and simulation tools such as Gazebo or MuJoCo. - Exposure to real-time embedded control systems and hardware deployment. - Experience with Reinforcement Learning (RL) for control or locomotion tasks would be a nice to have. As a Control Engineer, you will play a vital role in supporting the deployment of stable and robust control on legged robotic platforms. Your primary responsibilities will include: - Designing, analyzing, and implementing control algorithms for legged locomotion systems. - Designing and deploying Model Predictive Controllers (MPC) for balancing and trajectory tracking. - Developing and tuning classical controllers such as PID, lead-lag, state-space, and observer-based controllers. - Analyzing system stability using Nyquist plots, Bode plots, root locus, Lyapunov stability, and frequency-domain methods. - Modeling and controlling nonlinear dynamic systems including inverted pendulum and double inverted pendulum systems. - Working on dynamic balancing, disturbance rejection, contact stability, and whole-body control concepts. - Validating controllers through simulation and real-world robotic deployment. To qualify for this role, you should have the following qualifications: - Minimum Masters degree in Robotics, Control Systems, Mechanical Engineering, Electrical Engineering, or a related field. - Strong background in Control Theory, Dynamics, and Robotics. - Experience with stability analysis and classical control methodologies. - Hands-on experience with MPC deployment in real-time systems. - Familiarity with legged robot dynamics and locomotion principles. - Proficiency in MATLAB/Simulink, Python, or C++. - Understanding of nonlinear systems and trajectory optimization is preferred. Additionally, the following experience would be preferred: - Experience with humanoids, quadrupeds, or double inverted pendulums systems. - Knowledge of ROS/ROS2 and simulation tools such as Gazebo or MuJoCo. - Exposure to real-time embedded control systems and hardware deployment. - Experience with Reinforcement Learning (RL) for control or locomotion tasks would be a nice to have.