3 accepted papers
Robotic deployments in human environments have motivated the need for autonomous systems to be able to interact with humans and solve tasks effectively. Human demonstrations of tasks can be used to infer underlying task specifications, commonly modeled with temporal logic. State-of-the-art methods h…
We present a framework for planning complex motor actions such as pouring or scooping from arbitrary start states in cluttered real-world scenes. Traditional approaches to such tasks use dynamic motion primitives (DMPs) learned from human demonstrations. We enhance a recently proposed state-of-the-a…
Recently, there has been a growing interest in robotic systems that are able to share workspaces and collaborate with humans. Such collaborative scenarios require efficient mechanisms to communicate human requests to a robot, as well as to transmit robot interpretations and intents to humans. Recent