Many advances in robotics come from simulated environments where you generate vast, labeled synthetic data to train and validate models quickly and cheaply; by controlling physics, lighting, and variability, you accelerate iteration, reduce reliance on costly real-world trials, and explore edge cases, while techniques like domain randomization and sim-to-real transfer help your policies generalize to […]
