Toyota Research Institute-02

Following the recent slew of new hires in January this year, another development has come about for the Toyota Research Institute (TRI). The Jaybridge Robotics software engineering team has joined TRI to expand the automaker’s goal of developing its autonomous vehicle tech.

“The 16-member Jaybridge team brings decades of experience developing, testing and supporting autonomous vehicle products which perfectly complements the world-class research team at TRI,” said CEO of TRI, Gill Pratt. The Jaybridge team will join the research institute’s Cambridge, Massachusetts facility.

There, the 16-member team will work closely with counterparts at TRI facilities across the US and also with partnering Toyota research and development teams all over the world. A background check of Jaybridge Robotics notes that it has worked on automation of industrial vehicles and autonomous systems that have “logged thousands of hours in the hands of end-users.”

“Where Jaybridge has historically limited its focus to industrial applications such as agriculture and mining, TRI is going after the big one: helping reduce the nearly 1.25 million traffic fatalities each year, worldwide,” said Jaybridge CEO, Jeremy Brown.


“TRI’s mission is to bridge the gap between research and product development in many areas including artificial intelligence, robotics and autonomous passenger vehicles,” Pratt reiterated.

First announced in November last year, TRI is an R&D enterprise that’s designed to bring fundamental research and product development closer together. Funded by an initial five-year USD$1 billion (RM4.1 billion) investment, its primary mandate is to enhance safety of automobiles, with the end being the creation of a car that’s incapable of crashing.

At the same time, it also aims to provide accessibility to those who cannot drive, including people with special needs and the elderly. Secondly, it’ll help turn outdoor mobility technology into products for indoor mobility. And last but not least, it’s meant to accelerate scientific discovery by applying techniques from artificial intelligence and machine learning.