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Deterministic Policy Gradient Based Robotic Path Planning with Continuous Action Spaces
2017
2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
One of the most important tasks for Autonomous Robotics is the ability to manipulate objects in real world unstructured environments. Traditional path planning for robotic manipulators requires precise location of the target object in the environment based on which inverse kinematics return the required joint-angles for approaching the object. This limits their use in real domains with dynamic relative positions of objects not being readily available. Recent work on deep reinforcement learning
doi:10.1109/iccvw.2017.91
dblp:conf/iccvw/PaulV17
fatcat:rmgorj3ka5annmf4o3gsrfo434