Perception

YOLO (You Only Look Once)

YOLO (You Only Look Once) is a family of real-time single-stage object detectors, introduced by Redmon et al. in 2016, that predict bounding boxes and class probabilities in one forward pass over the image instead of using a separate region-proposal stage. Successive versions from many maintainers improved accuracy while keeping inference fast enough for video rates on embedded GPUs, making YOLO the default detector in robotic vision pipelines.

Why it matters for physical AI

Perception has to fit the control loop's latency budget on onboard compute, and YOLO-class detectors are what make closed-loop object-aware behavior feasible on drones, mobile robots, and pick-and-place cells.