The video shows a KUKA robot that learns how to grasp and turn a valve autonomously. The robot learns not only how to achieve the goal of the task, but also how to react to different disturbances during the task execution. For example, the robot learns a reactive behavior that allows it to pause and resume the task in response to the changes of the uncertainty in the valve position. This helps the robot to avoid collision with the valve, and improves the reliability and robustness of the task execution.
The setup of this experiment comprises: the robot arm which is a KUKA LWR (Lightweight robotic arm), an Optitrack system for motion capture, a T-bar valve with adjustable friction level.
The initial task demonstration and reproduction phases are performed with kinesthetic teaching. The reactive behavior is implemented using a Reactive Fuzzy Decision Maker (RFDM).
The valve turning task is challenging, especially if the valve is moving dynamically. A similar valve-turning task is also included in the DARPA robot competition (DRC). However, in that challenge the valves are fixed, while here the valve is moving, which makes it even more difficult to accomplish the task.
Publication:
http://kormushev.com/papers/Ahmadzadeh_ICRA-2013.pdf
Citation:
Seyed Reza Ahmadzadeh, Petar Kormushev and Darwin G. Caldwell. Autonomous Robotic Valve Turning: A Hierarchical Learning Approach. IEEE Intl. Conf. on Robotics and Automation (ICRA 2013), Karlsruhe, Germany, 2013.