Research Engineer/Scientist, Physical Human-Robot Interaction (pHRI)
Robotics – Robotics /
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 Robotics, Human-Centered AI, Human Interactive Driving, and Energy & Materials.
Our collaborative Project Punyo 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 ergonomically safe pHRI policies/controllers learned from demonstrations by healthcare professionals; further, the pHRI algorithms will be personalized to each end-user so that they 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, designers, and roboticists. The RUXID team collaborates closely with several TRI's robotics engineering teams, specifically with the Whole Body Manipulation team for our Project Punyo.
- Develop provably ergonomically safe physical human-robot interactions learned/derived from expert human-human demonstrations (e.g., motion capture and various tactile sensors).
- Research methods for personalization of physical human-robot interactions derived from user needs of aging society.
- Develop and deploy controllers in a physics simulation and on real hardware that would then be tested on user studies with real people.
- Collaborate cross-functionally with user experience researchers and designers, roboticists, mechanical engineers, and software engineers.
- Follow software practices that produce maintainable code, including automated testing, continuous integration, code style conformity, and code review.
- Ph.D. (Robotics, Biomechanical / Biomedical Engineering, Computer Science, Human-Robot Interaction, or related engineering field) OR equivalent practical experience.
- Experience with high DoF (degrees of freedom) robots in the real world, such as robot arms, mobile manipulators, and humanoids.
- Knowledge of key robotics areas such as trajectory optimization, model based planners, reactive planning and controls, compliant motion control, soft-contact modeling, 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) 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.
- Desire to iterate on concepts to include end-user or Subject Matter Expert feedback and prove out concepts in user studies.
- A team player 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.
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