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Evaluate a bimanual robot arm for research with a practical framework for synchronization, reach, calibration, sensing, software, and support.

Explore embodied AI hardware for repeatable robot learning, from manipulators and grippers to cameras, compute, controllers, mobile bases, and interfaces.

Explore physical ai startup decisions for hardware, software, data workflows, and support, from first prototype through a repeatable pilot.

Learn how to integrate a robot arm ROS workflow for research, then build a repeatable path from motion and sensing to safe, synchronized data capture.

Evaluate a robotics workstation for physical AI with a scorecard covering GPU, CPU, memory, storage, CUDA, ROS, simulation, data, and total cost.