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Efficient and robust grasp planning based on independent contact region and caging |
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| รหัสดีโอไอ | |
| Title | Efficient and robust grasp planning based on independent contact region and caging |
| Creator | Teesit Makapunyo |
| Contributor | Attawith Sudsang |
| Publisher | Chulalongkorn University |
| Publication Year | 2560 |
| Keyword | Robots, Robust control, Neural networks (Computer science), หุ่นยนต์, การควบคุมโรบัสต์, นิวรัลเน็ตเวิร์ค (วิทยาการคอมพิวเตอร์) |
| Abstract | A conventional way to find a proper grasp to grab and hold any object is to measure its stability which usually is based on physical constraint called force-closure. This execution works well from the theoretical point of view but often fails on an actual robot due to many reasons such as intrinsic errors in robot’s system and a disparity between real and simulated physics. Several research works introduced methods to alleviate those issues and increase the success rate of grasping for a real robot. Caging and Independent Contact Region are ones of them. In this work, we investigate a method to find a grasp that is more stable and robust by combining those two techniques which result in a learning-based approach that utilizes an artificial neural network to find a proper grasp based on those techniques and some heuristic methods. |
| URL Website | cuir.car.chula.ac.th |
