Toyota announced a research center in Ann Arbor, near the University of Michigan (U-M) campus. CEO Dr. Gill Pratt announced the venture at the GPU Technology conference in San Jose.
Toyota will fund research in artificial intelligence, robotics and materials science. Joining other Toyota Research Institute centers established in Palo Alto working with Stanford (TRI-PAL), and in Cambridge working with MIT (TRI-CAM), the TRI-ANN is scheduled to open in June and target a staff of approximately 50.
The Toyota Technical Centers researched autonomous cars for more than a decade. A group of about 15 team members will transfer to the new TRI-ANN facility when it opens. U-M Professors Ryan Eustice and Edwin Olson are joining TRI-ANN as the area leads for mapping/localization and perception, respectively. Both will be based at the Ann Arbor office, and will retain their U-M faculty positions.
Although the focus of each of the three strategically located facilities will be broad, each will feature a different core discipline. TRI-ANN will focus primarily on fully autonomous (chauffeured) driving. TRI-PAL will work on what may be termed “guardian angel” driving, where the driver is always engaged but the vehicle assists as needed. TRI-CAM will dedicate a large portion of its work to simulation and deep learning.
The Toyota Research Institute is an enterprise designed to bridge the gap between fundamental research and product development. With initial funding of $1 billion, it has four initial mandates.
- To enhance the safety of automobiles with the ultimate goal of creating a car that is incapable of causing a crash, regardless of the skill or condition of the driver.
- To increase access to cars to those who otherwise cannot drive, including seniors and those with special needs.
- To help translate Toyota’s expertise in creating products for outdoor mobility into products for indoor mobility; moving people and goods across the country, across town, or across the room.
- To accelerate scientific discovery by applying techniques from artificial intelligence and machine learning, particularly in the area of materials science. Using computation and machine learning, it hopes to accelerate scientific discovery in this area, lowering costs and improving performance of future mobility systems.
Beyond the projects it will engage in with the three universities (more than 30 are already underway at Stanford and MIT), TRI is enthusiastically pursuing collaboration with other automakers, IT companies, suppliers, research labs and universities to jointly develop autonomous technologies.