Statistical Stratification and Benchmarking of Robotic Grasping Performance
Author:
Affiliation:
1. School of Electronic Engineering and Computer Science, Queen Mary University of London, London, U.K.
2. The Shadow Robot Company, London, U.K.
Funder
Engineering and Physical Sciences Research Council
HuMAN-inspired robotic MANipulation for advanced MANufacturing
Shadow Robot Company
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/8860/10352149/10242148.pdf?arnumber=10242148
Reference41 articles.
1. Challenges for robot manipulation in human environments [Grand Challenges of Robotics]
2. Design of Artificial Hands: A Review
3. Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Data
4. Deep object pose estimation for semantic robotic grasping of household objects;Tremblay,2018
5. Vision-based robotic grasping from object localization, object pose estimation to grasp estimation for parallel grippers: a review
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