Research Engineer/Scientist

Human-Robot Interaction, Hri

Confirmed live in the last 24 hours

51-200 employees

Website

R&D arm of Toyota

Company Overview

Toyota Research Institute's mission is to improve the quality of human life through advances in artificial intelligence, automated driving, robotics, and materials science. They're dedicated to building a world of “mobility for all” where everyone, regardless of age or ability, can live in harmony with technology to enjoy a better life.

Locations

Cambridge, MA, USA

Experience Level

Entry

Junior

Mid

Senior

Expert

Desired Skills

Python

Communications

CategoriesNew

Mechanical Engineering

Requirements

M.S. or Ph.D. (Robotics, Biomechanical / Biomedical Engineering, Computer Science, Human-Robot Interaction, or related engineering field) OR equivalent practical experience
Knowledge of key robotics areas such as trajectory optimization, sampling based planners, reactive planning and control, compliant motion control, modeling soft-contact, and coordinated whole-body control
Experience in applying machine learning to real robots, including areas such as reinforcement, imitation, and sim2real transfer
Experience with robotic applications that involve humans in the loop, including human intent estimation and testing out proof of concepts with users
Experience with and understanding of multi-modal sensing including visual perception (e.g., cameras, lidar) and force/contact sensors (e.g., force-torque sensors, pressure/tactile sensing)
Strong software engineering skills, preferably in C++ and Python, and experience deploying onto physical robotic systems, including strong analysis and debugging skills
Experience with robotic system integration in the context of complex, open-ended, cross-functional projects
Experience with deployment of high DoF (degrees of freedom) robots in the real world (i.e., home settings) for extended periods and debugging/servicing as needed
Desire to iterate on concepts to include end-user or Subject Matter Expert feedback and prove out concepts in user studies
A great teammate with strong communication skills, and a willingness to learn from others and contribute back to the robotics community with publications and open source code
Passion for seeing robotics help humans and desire to have a real-world, large-scale impact

Responsibilities

Research formal methods for safe hands-on, physical human-robot interactions derived from user needs of aging society
Develop provably ergonomically safe physical human-robot interactions derived from expert human-human demonstrations
Collect multi-modal data sets (motion capture and various tactile sensors) of expert demonstrations for controller development
Develop and deploy these algorithmic solutions in a physics-based simulation and on real hardware and conduct user studies with real people
Collaborate cross-functionally with user experience researchers and designers, roboticists, and software engineers
Follow software practices that produce maintainable code, including automated testing, continuous integration, code style conformity, and code review

At Toyota Research Institute (TRI), we’re on a mission to improve the quality of human life. We’re developing new tools and capabilities to amplify the human experience. To lead this transformative shift in mobility, we’ve built a world-class team in Human-Centered AI, Human Interactive Driving, Energy and Materials, Machine Learning, and Robotics!

Our HASTEN (Helping Aging Society: Tactile Embodied Nudging) collaborative team brings together complementary research and engineering expertise in physical human-robot interaction, bubblized soft robotics, humanoid systems, software development, user-centered design, and occupational and physical therapy experts. Our team develops robotic technology, sensing, and algorithms for supporting older adults in their homes with activities of daily living that require large amounts of surface contact between people and robots in order for robots to provide supportive assistance, in the context of stability and mobility such as getting up from a chair and dressing.

In these close proximity and directly hands-on physical contact human-robot interactions, safety is paramount! Therefore, the focus of this role will be to develop pHRI algorithms that are robust and provably biomechanically sound such that our end-users feel secure and comfortable when being supported and assisted by our robots. This role is on the RUXID (Robotics UX & Interaction Design) team, which comprises UX researchers and designers, as well as HRI researchers. The RUXID team collaborates closely with TRI’s robotics engineering teams.

Responsibilities

Research formal methods for safe hands-on, physical human-robot interactions derived from user needs of aging society.
Develop provably ergonomically safe physical human-robot interactions derived from expert human-human demonstrations.
Collect multi-modal data sets (motion capture and various tactile sensors) of expert demonstrations for controller development.
Develop and deploy these algorithmic solutions in a physics-based simulation and on real hardware and conduct user studies with real people.
Collaborate cross-functionally with user experience researchers and designers, roboticists, and software engineers.
Follow software practices that produce maintainable code, including automated testing, continuous integration, code style conformity, and code review.

Qualifications

M.S. or Ph.D. (Robotics, Biomechanical / Biomedical Engineering, Computer Science, Human-Robot Interaction, or related engineering field) OR equivalent practical experience.
Knowledge of key robotics areas such as trajectory optimization, sampling based planners, reactive planning and control, compliant motion control, modeling soft-contact, and coordinated whole-body control.
Experience in applying machine learning to real robots, including areas such as reinforcement, imitation, and sim2real transfer.
Experience with robotic applications that involve humans in the loop, including human intent estimation and testing out proof of concepts with users.
Experience with and understanding of multi-modal sensing including visual perception (e.g., cameras, lidar) and force/contact sensors (e.g., force-torque sensors, pressure/tactile sensing).
Strong software engineering skills, preferably in C++ and Python, and experience deploying onto physical robotic systems, including strong analysis and debugging skills.
Experience with robotic system integration in the context of complex, open-ended, cross-functional projects.
Experience with deployment of high DoF (degrees of freedom) robots in the real world (i.e., home settings) for extended periods and debugging/servicing as needed.
Desire to iterate on concepts to include end-user or Subject Matter Expert feedback and prove out concepts in user studies.
A great teammate with strong communication skills, and a willingness to learn from others and contribute back to the robotics community with publications and open source code.
Passion for seeing robotics help humans and desire to have a real-world, large-scale impact.

Please reference this Candidate Privacy Notice to inform you of the categories of personal information that we collect from individuals who inquire about and/or apply to work for Toyota Research Institute, Inc. or its subsidiaries, including Toyota A.I. Ventures GP, L.P., and the purposes for which we use such personal information.

TRI is fueled by a diverse and inclusive community of people with unique backgrounds, education and life experiences. We are dedicated to fostering an innovative and collaborative environment by living the values that are an essential part of our culture. We believe diversity makes us stronger and are proud to provide Equal Employment Opportunity for all, without regard to an applicant’s race, color, creed, gender, gender identity or expression, sexual orientation, national origin, age, physical or mental disability, medical condition, religion, marital status, genetic information, veteran status, or any other status protected under federal, state or local laws.