Multi-View Picking: Next-best-view Reaching for Improved Grasping in Clutter

September 23, 2018 · Entered Twilight · 🏛 IEEE International Conference on Robotics and Automation

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Repo contents: .gitignore, LICENSE, README.md, cad, dougsm_helpers, franka_control_wrappers, ggcnn, mvp_grasping, requirements.txt, scales_interface

Authors Douglas Morrison, Peter Corke, Jürgen Leitner arXiv ID 1809.08564 Category cs.RO: Robotics Citations 86 Venue IEEE International Conference on Robotics and Automation Repository https://github.com/dougsm/mvp_grasp ⭐ 231 Last Checked 1 month ago

Abstract

Camera viewpoint selection is an important aspect of visual grasp detection, especially in clutter where many occlusions are present. Where other approaches use a static camera position or fixed data collection routines, our Multi-View Picking (MVP) controller uses an active perception approach to choose informative viewpoints based directly on a distribution of grasp pose estimates in real time, reducing uncertainty in the grasp poses caused by clutter and occlusions. In trials of grasping 20 objects from clutter, our MVP controller achieves 80% grasp success, outperforming a single-viewpoint grasp detector by 12%. We also show that our approach is both more accurate and more efficient than approaches which consider multiple fixed viewpoints.