Toyota-Hyundai partnership to research humanoid technology

News Story
- 31 Oct 2024 ( #1203 ) - Boston, United States
1 min read
Two motor giant join forces to research humanoid technology
Two motor giant join forces to research humanoid technology

A new research agreement aimed at accelerating the development of general purpose humanoid robots, has been announced between Toyota Research Institute (TRI) and Boston Dynamics.

TRI is the AI and automation R&D arm of Toyota Motor Corporation while Boston Dynamics was acquired by Hyundai Motor Group in 2020 and deploys highly mobile robots within a number of sectors including the warehouse-specific robot Stretch.

The research partnership will integrate TRI’s large behaviour models with Boston Dynamics electric humanoid robot Atlas.

Boston Dynamics describes Atlas as “the result of years of hardware/software co-design aimed at building the most capable humanoid platform, both in terms of physical capability and software interfaces for authoring whole-body behaviours”.

Boston Dynamics chief executive office Robert Playter says of the partnership: “There has never been a more exciting time for the robotics industry, and we look forward to working with TRI to accelerate the development of general-purpose humanoids”.

Boston Dynamics states the research team will also “conduct research to answer fundamental training questions for humanoid robots, the ability of research models to leverage whole-body sensing, and understanding human-robot interaction and safety/assurance cases”.

“The project is designed to leverage the strengths and expertise of each partner equally,” Boston Dynamics’ statement continues. “The physical capabilities of the new electric Atlas robot, coupled with the ability to programmatically command and tele-operate a broad range of whole-body bimanual manipulation behaviours, will allow research teams to deploy the robot across a range of tasks and collect data on its performance. 

“This data will, in turn, be used to support the training of advanced LBMs, utilising rigorous hardware and simulation evaluation to demonstrate that large, pre-trained models can enable the rapid acquisition of new robust, dexterous, whole-body skills.”

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