Abstract: A computing system may include a fail-safe learning engine configured to access camera data captured by multiple cameras positioned within an environment during a learning phase, generate training data based on the camera data captured by the multiple cameras, and construct a human detection model using the training data. The computing system may also include a fail-safe trigger engine configured to access camera data captured by the multiple cameras positioned within the environment during an active phase, and the camera data captured during the active phase may include a target object. The fail-trigger engine may further be configured to provide, as an input to the human detection model, the camera data that includes the target object and execute a fail-safe action in the environment responsive to the determination, provided by the human detection model, indicating that the target object is a human.

Abstract: A computing system may include a fail-safe learning engine configured to access camera data captured by multiple cameras positioned within an environment during a learning phase, generate training data based on the camera data captured by the multiple cameras, and construct a human detection model using the training data. The computing system may also include a fail-safe trigger engine configured to access camera data captured by the multiple cameras positioned within the environment during an active phase, and the camera data captured during the active phase may include a target object. The fail-trigger engine may further be configured to provide, as an input to the human detection model, the camera data that includes the target object and execute a fail-safe action in the environment responsive to the determination, provided by the human detection model, indicating that the target object is a human.

Abstract: A system and method for modeling human behavior includes receiving, by a classifier module, sensor data from one or more sensors monitoring human behavior associated with a work task and to identify the type of human behavior based on a trained neural network. A prediction module receives the identified type of human behavior from the classifier and generates prediction data representing predicted next one or more human actions based on a time series of position vectors learned by the trained neural network. A rendering module translates the prediction data into a visual rendering for a virtual human simulation model.