IRR - Honda Research Institute USA
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Intelligence Robotics Research
Honda Research Institute USA Is Accepting University Project Proposals
Shaping the Future of Embodied Intelligence and Dexterity
About us
The Intelligence Robotics Research (IRR) Division at Honda Research Institute USA (HRI-US) conducts foundational research that advances the frontier of dexterous manipulation, multimodal perception, and interfaces beyond the current state of human-robot-interaction – into true automation and human-robot collaboration. Working closely with Honda R&D’s Frontier Robotics Domain, we explore the core scientific challenges that will enable the next generation of avatar-type-systems robots capable of performing sophisticated tasks in environments where human presence cannot be immediate, is difficult, dangerous, or even impossible.
Our work focuses on the fundamental capabilities that make these systems viable. We look beyond hardware novelties and instead focus on next-generation hardware mated with novel software interaction that – together – create a new model, and enable naturalistic shared autonomy.
Together, Honda R&D’s exceptional hardware expertise, and the fundamental computer science research that takes place within IRR, are already showcasing that autonomy can lower the skill barrier for teleoperation, tactile-driven in-hand object understanding, the use of geometry-based force estimation to expand manipulation strategies, and methods for translating human-hand motion to robotic hands with very different kinematics.
Our work focuses on the fundamental capabilities that make these systems viable. We look beyond hardware novelties and instead focus on next-generation hardware mated with novel software interaction that – together – create a new model, and enable naturalistic shared autonomy.
Together, Honda R&D’s exceptional hardware expertise, and the fundamental computer science research that takes place within IRR, are already showcasing that autonomy can lower the skill barrier for teleoperation, tactile-driven in-hand object understanding, the use of geometry-based force estimation to expand manipulation strategies, and methods for translating human-hand motion to robotic hands with very different kinematics.