Research Engineer Contractor: Motion Planning and Control for Marine Robotics

Honda Research Institute USA; San Jose (CA); On-site; USD 124,000 - 165,000; Full time

Job summary

Honda Research Institute USA in San Jose, CA, seeks a Research Engineer Contractor to advance motion planning and control for marine robotics. The role supports trajectory planning, vessel dynamics, and field trials with ROS/Python/C++ development.

The position focuses on research and prototype development, collaboration with AI and robotics experts, and dissemination of results through papers and presentations.

Qualifications

• Master's degree in a relevant field.
• 2+ years coding in robotics-relevant tools (Python, MATLAB, C/C++).
• Experience in motion planning, reference trajectories, and control.
• Experience solving loosely defined research problems.
• Experience with machine learning algorithms and AI methodologies.

Responsibilities

• Conduct research in marine robotics focusing on trajectory planning and control.
• Develop vessel dynamics models and perform system identification from data.
• Design planning/control methods robust to disturbances and constraints.
• Develop software for prototypes and field tests using ROS and Python/C++.
• Collaborate with AI experts and publish results; support documentation.

Skills

Motion planning

Trajectory generation

Control systems

Robotics problem solving

Python

C/C++

MATLAB

ROS/ROS2

Machine learning basics

Education

Master's degree in Robotics Engineering/ Naval Engineering / ML / Stat / Mech / EE

Tools

ROS1/ROS2

Python

C++

MATLAB

Job description

Research Engineer Contractor: Motion Planning and Control for Marine Robotics - Honda Research Institute USA

Job Number: P25T07

Honda Research Institute USA (HRI-US) is seeking a motion planning and controls researcher/engineer to support research in the marine environment and autonomous vessel domain. The ideal candidate understands trajectory planning, advanced control, reference trajectory/path generation, and system modeling, and can connect these methods to real systems through simulation and field evaluation. You will work on vessel trajectory planning and control and collaborate with Al and Robotics experts, global Honda researchers, and academic partners on research projects and on-water/field trials.

San Jose, CA

Key Responsibilities

• Conduct research in marine robotics with focus on trajectory planning, control, reference paths, and system modeling
• Stay current with planning/control approaches including MPC, MPPI, and other optimization- and sampling-based methods
• Develop and validate vessel dynamics models, including system identification and parameter estimation from simulation and field data
• Design planning/control methods that are robust to disturbances and uncertainty (wind/waves/current, model mismatch), including constraint handling and actuator limits
• Develop software for early-stage prototypes and proof-of-concept systems (strong experience with ROS2/ROS1, Python, C++)
• Run simulation studies and conduct target/field tests; evaluate robustness, stability, and tracking performance under realistic disturbances
• Work with localization/state information and integrate planning/control with vehicle interfaces and actuators
• Apply and leverage machine learning/AI concepts where relevant (e.g., learned models, prediction, learned cost components)
• Assist in documentation: papers, slides, and tech transfer material
• Participate in brainstorming activities and cross-functional collaborations related to autonomous vessel research

Minimum Qualifications

• Master's degree in Robotics Engineering, Naval Engineering, Machine Learning, Statistics, Mechanical Engineering, Electrical Engineering, or similar
• Demonstrated experience in motion planning, reference trajectories, and control
• Demonstrated experience solving loosely defined research/engineering problems
• 2+ years coding in robotics-relevant tools/languages (e.g., Python, MATLAB, C/C++)
• Experience creating and using advanced control and motion planning methods
• Experience with machine learning algorithms and AI methodologies

Bonus Qualifications

• Experience with robotics systems overall; familiarity with perception/tracking interfaces is a plus
• Experience with system identification, model calibration, or data-driven dynamics modeling
• Experience with robust/adaptive control or uncertainty-aware MPC formulations (e.g., disturbance observers, constraint tightening), as applicable
• Familiarity with marine robotics and USV/ASV challenges (environmental disturbances, sensing limitations, operational constraints)
• Experience programming within Unix-based operating systems (e.g., Linux)
• Programming in Python, ROS1/ROS2, and observer/state-space modeling concepts

Desired Start Date 10/05/2026

Contract Duration 2years

Position Keywords Robotics, Motion Planning, Control, USV, System Identification