Motion Simulator Washout Algorithms Expert

Are you passionate about human space exploration, understanding the origins of the universe, and working with a passionate and diverse team to make a difference? If you are, we need you!

We need your talent, teamwork, and energy to help us achieve great things that inspire people all over the globe. We need you to bring creative ideas and diverse backgrounds to help us envision, shape, and deliver systems that will enable the exploration of space while benefiting people here on Earth. We are excited about what we do, and we need you on our team as we take on exciting challenges for NASA’s pursuits in deep space exploration.

As NASA’s largest engineering solutions provider working together with NASA at centers across the United States.

We have an exciting opportunity for a part-time Motion Simulator Washout Algorithms Expert to join the JETSII Contract!

The Motion Simulator Washout Algorithms Expert is responsible for the research, design, development, validation, and optimization of advanced motion cueing and washout algorithms for high-fidelity motion simulation systems. The successful candidate will serve as a technical leader in the development of novel motion cueing methodologies that maximize motion realism while respecting physical limitations of motion platforms such as Stewart platforms, hexapod systems, cable-driven robots, and other parallel-actuated simulators.

Key Responsibilities:

• Develop advanced motion cueing and washout algorithms for six-degree-of-freedom (6
  
  DOF) motion simulators.
• Design adaptive, model-based, optimal, and nonlinear washout filters to improve simulator fidelity and user realism.
• Research human vestibular and motion perception characteristics to enhance simulator performance.
• Create mathematical models that reproduce translational and rotational motion cues within workspace constraints.
• Evaluate classical, optimal-control, machine learning, and hybrid approaches to motion cueing.
• Support development of washout filters for lunar, planetary, rover, lander, and spacecraft simulation systems.
• Develop dynamic models of motion platforms.
• Perform kinematic and dynamic analyses using matrix methods, Lie derivatives, quaternions, and dual quaternions.
• Design and implement advanced control systems for parallel manipulators and motion simulators.
• Conduct stability, robustness, and performance analysis of control architectures.
• Develop numerical methods for constrained, under-actuated, and over-actuated systems.
• Architect and develop simulation software for motion platform control and validation.
• Implement algorithms in C++, Python, MATLAB/Simulink, ROS, NASA Trick, or similar simulation environments.
• Develop real-time motion cueing software for hardware-in-the-loop test facilities.
• Create software tools for visualization, tuning, testing, and performance assessment.
• Support integration of simulator software with vehicle dynamics models.
• Perform frequency-domain and time-domain performance evaluations.
• Analyze subjective and objective metrics of motion realism.
• Develop validation methodologies correlating simulated motion with target vehicle dynamics.
• Support simulator acceptance testing and operational readiness reviews.

• Typically, educational requirements are the equivalent of a BS with at least 20 years of experience.
• Ph.D. in Mathematics, Applied Mathematics, Physics, or related technical discipline and a minimum of (20) years of experience in applied mathematics.
  • Demonstrated experience developing advanced mathematical models for dynamic systems.
  • Experience with motion simulation, robotics, control systems, or vehicle dynamics.
  • Experience designing numerical algorithms and simulation software.
• Technical Knowledge:
  • Motion cueing and washout algorithm design.
  • Classical and modern control theory.
  • Optimization methods.
  • State-space modeling.
  • Dynamic systems analysis.
  • Parallel robot kinematics and dynamics.
  • Stewart platforms and hexapod motion systems.
  • Numerical methods and scientific computing.
  • Real-time simulation architectures.

• Python
• C++
• MATLAB/Simulink
• ROS
• NASA Trick
• Linux/Unix environments
• Mathematica
• Scientific visualization tools

• Experience…