We present a learning and control strategy that enables robots to harness physical human
interventions to update their trajectory and goal during autonomous tasks. Within the state of …

Humans can leverage physical interaction to teach robot arms. This physical interaction
takes multiple forms depending on the task, the user, and what the robot has learned so far …

We focus on learning robot objective functions from human guidance: specifically, from
physical corrections provided by the person while the robot is acting. Objective functions are …

Robots are moving from working in isolated cham-bers to working in close-proximity with
human collaborator (s) as part of human-robot teams. In such situations, robots are …

When a robot performs a task next to a human, physical interaction is inevitable: the human
might push, pull, twist, or guide the robot. The state of the art treats these interactions as …

When humans and robots work in close proximity, physical interaction is inevitable.
Traditionally, robots treat physical interaction as a disturbance, and resume their original …

During human-robot interaction, we want the robot to understand us, and we want to
intuitively understand the robot. In order to communicate with and understand the robot, we …

Despite tremendous advances in robotics, we are still amazed by the proficiency with which
humans perform movements. Even new waves of robotic systems still rely heavily on …

Ideally, we would place a robot in a real-world environment and leave it there improving on
its own by gathering more experience autonomously. However, algorithms for autonomous …

When personal, assistive, and interactive robots make mistakes, humans naturally and
intuitively correct those mistakes through physical interaction. In simple situations, one …