Kramer is a helpful robot in assembling block structures. It can work collaboratively with humans on various assembly tasks. Kramer is capable of learning from human collaborations and construct planning models accordingly to synthesize coordination plans that are “explainable” to humans.
Sprinkles is a robot based on PeopleBot mobile platform that is designed to help with office tasks such as sensing and delivery. It can take simple requests such as “Deliver this Room 566”, autonomously plans a path to get to the destination. It is currently deployed on the 5th floor of the CS department. Sprinkles interacts with humans by utilizing facial recognition software, voice prompts and speech recognition, as well as touch input from an onboard web application. It uses a Microsoft Kinect sensor and a built-in ultrasonic sensor for mapping and obstacle avoidance. To satisfy user commands, Sprinkles uses an automated planner to generate a course of action, and executes it.
We aim to develop a way of mapping high level tasks to low level trajectories. We start with the assumption, that any given grounded action can map to multiple DMPs and in our approach we attempt to map the action to a single DMP based on the action’s context with in the plan. In the video on the left, Newman performs a lateral pickup on the cup, since it later needs to perform a pour action. In the video on the right, we perform a vertical pickup on the cup, since it only needs to place the cup at a different position.