Planning Multi-fingered Grasps as Probabilistic Inference in a Learned Deep Network
- 28 November 2019
- book chapter
- Published by Springer Nature
- p. 455-472
Abstract
No abstract availableKeywords
All Related Versions
This publication has 21 references indexed in Scilit:
- Generating multi-fingered robotic grasps via deep learning2015
- The YCB object and Model set: Towards common benchmarks for manipulation research2015
- Leveraging big data for grasp planning2015
- Real-time grasp detection using convolutional neural networks2015
- Deep learning for detecting robotic graspsThe International Journal of Robotics Research, 2015
- BigBIRD: A large-scale 3D database of object instances2014
- An overview of 3D object grasp synthesis algorithmsRobotics and Autonomous Systems, 2012
- BlenSor: Blender Sensor Simulation Toolbox2011
- Robotic Grasping of Novel Objects using VisionThe International Journal of Robotics Research, 2008
- Dimensionality reduction for hand-independent dexterous robotic grasping2007