A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI
This survey examines how physics simulators are used to train embodied AI for robotic navigation and manipulation by bridging the gap between simulation and real-world performance. It categorizes challenges like perception and action-dynamics gaps, reviews various simulators like MuJoCo, and discusses memory representations essential for agents to learn complex skills safely before deployment on hardware.