Research Intern: Vehicle Dynamics and Simulation Marine Robotics

Research Intern:
Vehicle Dynamics and Simulation for Marine Robotics - Honda Research Institute USA Research Intern:
Vehicle Dynamics and Simulation for Marine Robotics

Job Number: P25IN
T-67

Honda Research Institute USA (HRI-US) is seeking a self-motivated research intern to develop the marine vehicle capability of our Unreal Engine 5 simulator. You will set up and tune vessel hydrodynamics and multi-engine propulsion in UE5 and package them as reusable simulator plugins. The goal is to build a simulator that reflects real on-water vessel behavior closely enough to generate synthetic data and run closed-loop experiments ahead of field testing.

San Jose, CA

• Develop the marine-specific vehicle platform and water environment in the UE5 simulator — the foundation the hydrodynamics and propulsion work build on.
• Implement and tune hydrodynamics in the UE5 environment — buoyancy, wave and current forcing, and wind disturbance — so vessel motion responds realistically to conditions.
• Implement a multi-engine (twin-engine) propulsion model, including thrust allocation and differential-thrust maneuvering.
• Integrate the above as modular simulator plugins exposed through ROS 2 interfaces for scenario generation.
• Validate simulated vessel motion against reference behavior; document assumptions and limitations.

• M.S. candidate in robotics, mechanical/aerospace engineering, or a related field.
• Working experience with Unreal Engine 5 (C++ and/or Blueprints).
• Solid grounding in rigid-body dynamics and physics-based simulation.
• Proficiency in C++ and Python.
• Experience with ROS 2.

• Ph.D. candidate in a related field.
• Background in marine/vehicle dynamics, hydrodynamics, or naval architecture.
• Experience developing custom plugins for a UE5-based simulator.
• Experience with closed-loop, physics-based vehicle simulation under environmental disturbances (wind, waves, currents).
• Experience modeling propulsion or thrust allocation.
• Solid understanding of classical motion planning & control, including Model Predictive Control (MPC).
• Prior experience taking simulation models toward real-world validation.