About
Operator
Industrial Next is building intelligent robots for manufacturing and beyond, powered by its own robotics foundation model and a Real2Sim2Real pipeline. As the operator of Sim2World, it provides real-world infrastructure where researchers and industry teams can test ideas, evaluate policies, and address the challenges of deploying robots at scale.
Real2Sim Partner
Versor is a new applied research lab solving general-purpose robotics by closing the loop on Real2Sim2Real. As the Real2Sim partner of Sim2World, Versor starts with a single robot trajectory and automatically generates simulations and expert robot behaviors that converge toward handling the full complexity of operating in the real world.
3D Asset Partner
ALLSIDES turns real-world objects into simulation-ready 3D assets through fully automated scanning in minutes. It supports Sim2World with these 3D assets and its CUBE 3D scanner, enabling teams to quickly digitize new objects for simulation and robot training. Its library offers millions of physically grounded SimReady 3D models.
Data Infra Partner
Paddy builds data infrastructure for physical AI. Its Harvester station, with dual xArm 7 arms and stereo depth cameras, records teleoperated demonstrations and validates policies on the same hardware. It supports Sim2World with real-world data and on-machine evaluation.
Academia
Our startup and academic partners jointly identify key gaps in Real2Sim2Real. Academic collaborations explore these gaps through novel research, transparent methods, and fair evaluation. All results from these collaborations are open to publication.
Prof. Siddhartha Srinivasa (PRL) · University of Washington
Research spans perception, manipulation, learning, and human-robot interaction, enabling robots to work around people in cluttered, uncertain environments. Applications include assistive feeding and autonomous navigation.
Asst. Prof. Abhishek Gupta (WEIRD Lab) · University of Washington
Research focuses on algorithms and systems for robotic manipulation in the home, alongside computer vision, language modeling, and human-robot interaction. A central interest is making machine learning systems robust and reliable.
Assoc. Prof. Rika Antonova (CamRAL Lab) · University of Cambridge
Research combines reinforcement learning, global optimization, and scalable simulation for autonomous systems. The lab explores physics-informed reasoning, mobile manipulation, and the joint design of robot hardware and learned policies.
Industry Partners
We thank NVIDIA and Mitsubishi Electric for their continued support through infrastructure, compute resources, hardware, and productive commercial discussions.