Towards Autonomous Robotic Valve Turning
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In this paper an autonomous intervention robotic task to learn the skill of
grasping and turning a valve is described. To resolve this challenge a set of
different techniques are proposed, each one realizing a specific task and sending
information to the others in a Hardware-In-Loop (HIL) simulation. To improve the
estimation of the valve position, an Extended Kalman Filter is designed. Also to
learn the trajectory to follow with the robotic arm, Imitation Learning approach is
used. In addition, to perform safely the task a fuzzy system is developed which
generates appropriate decisions. Although the achievement of this task will be used
in an Autonomous Underwater Vehicle, for the first step this idea has been tested in
a laboratory environment with an available robot and a sensor