Learning the state of the world
Lawson L. S. Wong · AI Matters · 2017
Mobile-manipulation robots performing service tasks in human-centric indoor environments have long been a dream for developers of autonomous agents. Tasks such as cooking and cleaning involve interaction with the environment, hence robots need to know about their spatial surroundings. However, service robots operate in environments that are relatively unstructured and dynamic. Mobile-manipulation robots therefore need to continuously perform state estimation , using perceptual information to maintain a representation of the state, and its uncertainty, of the world.