Physical AI and robotics simulation are the keys to the success of robots moving goods, packaging foods and helping assemble vehicles for enhanced automation across industries.
Advanced robotics simulation helps in facilitating robot learning and testing of virtual robots without detracting the need for the physical robot.
Simulations are used for initial AI model training and to validate the software stack, reducing the need for physical robots during testing.
Robotics simulation is essential for enhancing planning, control and learning outcomes in complex and dynamic industrial settings.
High-fidelity, physics-based simulations have enhanced industrial robotics through real-world experimentation in virtual environments.
To close the sim-to-real gap, Isaac Lab offers a high-fidelity, open-source framework for reinforcement learning and imitation learning that facilitates seamless policy transfer from simulated environments to physical robots.
Robot developers can tap into NVIDIA Isaac Sim, which supports multiple robot training techniques.
Robotics simulation is used by global brands such as Delta Electronics, deep tech startup Wandelbots, Boston Dynamics, Fourier and robotics company Galbot.
Developers can also pair ROS 2 with Isaac Sim to train, simulate and validate their robot systems.
Through the continual development of robotics simulations and physical AI, robot technology and robot simulations dramatically improve operations across use cases.