Download or read book Robotic Grasping Using POMDPs and Machine Learning written by Ignacio Perez Bedoya and published by . This book was released on 2020 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robotic grasping is a fundamental problem in robotics. Currently, there is no single approach for finding good policies that are robust enough to deal with real-world uncertainty, a variety of different objects, and real-time execution. In this thesis, I designed and implemented a grasping algorithm that aims to address these shortcomings. The algorithm is based on two key ideas. First, it uses a POMDP to represent the grasping problem, a physics simulator to approximate the real world, and an offline POMDP solver to generate grasping policies. Then, it uses an RNN to learn from the generated policies given a variety of objects to create a real-time robust policy for grasping. Code can be found at [email protected]:ignapb/grasping.git