Human-Centered AI Intern

AI-generated virtual worlds accelerate robot training and development. July 15, 2026 Researchers have developed an AI-driven system that creates realistic virtual environments, enabling robots to practice complex tasks more efficiently before real-world deployment and testing. Researchers at the Massachusetts Institute of Technology (MIT) and the Toyota Research Institute have developed SceneSmith, an AI-powered framework that automatically generates realistic virtual environments for training robots. The system aims to reduce the time, cost and effort required to collect real-world training data while improving robots' ability to perform everyday tasks. Robots typically learn through repeated physical interactions, making the training process labour-intensive and expensive. SceneSmith addresses this challenge by creating detailed 3D indoor environments where robots can safely practise activities before operating in real-world settings. The framework relies on three AI agents working together throughout the design process. A "designer" creates the initial scene, a "critic" evaluates its realism and practicality, and an "orchestrator" manages revisions until the virtual environment meets the required standard. Once complete, the scenes are imported into physics simulation software that accurately models properties such as mass, friction and inertia. According to the researchers, the system generated more than 1,300 unique indoor environments, including homes, offices and commercial spaces. Compared with previous scene-generation methods, the environments contained significantly more objects and interactive elements, enabling robots to practise tasks such as opening cupboards, placing items on shelves and moving objects between rooms. The researchers also evaluated robot policies within these simulated environments before deployment. Human reviewers agreed with the AI system's assessments more than 99 per cent of the time, helping identify unsuitable strategies before physical testing began. Additional experiments showed that robots could interact with cabinets, bottles and other movable objects while maintaining realistic physical behaviour. User studies involving more than 200 participants found that the generated environments appeared realistic in over 90 per cent of cases and followed text prompts more accurately than earlier approaches. The researchers believe the technology could accelerate robotics development by providing scalable, diverse and highly realistic virtual training grounds while reducing dependence on costly real-world data collection.

Russ Tedrake to unveil stealth AI startup at Robotics Summit. Artificial intelligence has been dominating conversations at every technology event for the past few years, and the robotics industry continues to look for ways to apply the technology to robots. At the Robotics Summit & Expo, Russ Tedrake, a professor at MIT and former senior vice president of large behavior models (LBMs) at the Toyota Research Institute, will unveil his new stealth AI startup focused on deploying LBMs for robotics. Drawing on his deep experience in robotics and AI, Tedrake will share his vision for how physical AI can unlock more capable, adaptable robots across industries. The keynote, "Building Large Behavior Models for Industry," will examine the motivations behind the technology, early breakthroughs, and the potential impact of LBMs on next-generation robots. More about Russ Tedrake. Tedrake is the Toyota Professor of Electrical Engineering and Computer Science, Aeronautics and Astronautics, and Mechanical Engineering at MIT, the director of the Center for Robotics at the Computer Science and Artificial Intelligence Lab (MIT CSAIL), and the leader of Team MIT's entry in the DARPA Robotics Challenge. His research is focused on finding elegant control solutions for interesting - under-actuated, stochastic, or difficult-to-model - dynamical systems that he can build and experiment with. Tedrake is particularly interested in finding connections between mechanics, especially non-smooth mechanics, and machine learning or optimization theory, which enable robust control design for complex mechanical systems. Tedrake is a recipient of the 2021 Jamieson Teaching Award, the NSF CAREER Award, the MIT Jerome Saltzer Award for undergraduate teaching, the DARPA Young Faculty Award in Mathematics, and the 2012 Ruth and Joel Spira Teaching Award. He has also been named a Microsoft Research New Faculty Fellow. Registration is now open for the Robotics Summit & Expo, the world's leading technical event for commercial robotics developers. The event is produced by The Robot Report and parent company WTWH Media. The show will have more than 50 sessions in tracks on artificial intelligence, design and development, enabling technologies, healthcare, and logistics. The Engineering Theater on the show floor will also feature presentations by industry experts. The Robotics Summit will also feature a number of networking opportunities. These include a Mix & Mingle Networking Reception after the first day of the show, the ticketed RBR50 Awards Dinner, and a Women in Robotics Breakfast. The Robotics Summit & Expo is co-located with DeviceTalks Boston, which focuses on medical devices.