The Soft Bubble Gripper uses visuo-tactile sensing techniques that allow a robot to recognize objects by shape, track their orientation in its grasp and sense forces as it interacts with the world.
Phoenix Instinct team wins $1M first prize in Toyota Mobility Unlimited Challenge
Phoenix Instinct, one oof the five finalists in the Mobility Unlimited Challenge run by the Toyota Mobility Foundation and Nesta Challenges,
Neural network plus motion planning equals more useful robots, finds UC Berkeley
Researchers at the University of California, Berkeley, said that combining neural networks with motion-planning software will give robots the speed and skill to assist in warehouse environments.
Toyota Research Institute shows service robot prototypes in virtual open house
Toyota Research Institute demonstrated its research into machine learning, simulation, and manipulation in a virtual open house, which included a ceiling-mounted kitchen gantry robot.
Soft Bubble Gripper a step toward domestic robots, says Toyota Research Institute
The Soft Bubble Gripper developed by a Toyota Research Institute team combines sensors and advanced materials to more safely handle objects in a step toward household robots.
Woven Capital to be unified $800M fund from Toyota Research Institute – Advanced Development
Toyota Research Institute – Advanced Development has announced Woven Capital, a new $800 million fund that it said will consolidate support for R&D into smart cities, connected vehicles, and autonomous vehicles.
Toyota AI Ventures extends call for connected city innovations
Toyota AI Ventures has renewed its call for innovative startups to submit technologies that solve urban challenges for up to $2 million in funding.
CARMERA maps could benefit both autonomous vehicles and cities
CARMERA has been using cameras to build maps that could be valuable, not only for developers of autonomous vehicles, but also to urban transportation authorities.
Simulation engine from MIT trains self-driving cars before they hit real roads
A photorealistic simulation system enables autonomous vehicles to learn to drive in the real world and recover from near-crash scenarios.
Merging at tricky intersections gets easier for self-driving cars with MIT, TRI model
MIT and Toyota researchers have developed a model to alert driverless cars when it’s safest to merge into traffic at intersections with obstructed views.
Toyota Research Institute teaches mobile manipulator with VR, simulation
Toyota Research Institute shared its latest research on how to train a mobile manipulator for complex household tasks.