International Journal of Robotics Research
Robot grasp synthesis algorithms: a survey
International Journal of Robotics Research
Shape Matching and Object Recognition Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian Hierarchical Model for Learning Natural Scene Categories
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Efficient Shape Matching Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Pattern Recognition and Machine Learning (Information Science and Statistics)
Pattern Recognition and Machine Learning (Information Science and Statistics)
Groups of Adjacent Contour Segments for Object Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning grasp strategies with partial shape information
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Gaussian process latent variable models for human pose estimation
MLMI'07 Proceedings of the 4th international conference on Machine learning for multimodal interaction
Functional object class detection based on learned affordance cues
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Autonomous Robots
An overview of 3D object grasp synthesis algorithms
Robotics and Autonomous Systems
Efficient models for grasp planning with a multi-fingered hand
Robotics and Autonomous Systems
BADGr-A toolbox for box-based approximation, decomposition and GRasping
Robotics and Autonomous Systems
Extracting data from human manipulation of objects towards improving autonomous robotic grasping
Robotics and Autonomous Systems
Adaptive neuro fuzzy controller for adaptive compliant robotic gripper
Expert Systems with Applications: An International Journal
Enabling grasping of unknown objects through a synergistic use of edge and surface information
International Journal of Robotics Research
Design of a flexible tactile sensor for classification of rigid and deformable objects
Robotics and Autonomous Systems
Stable grasping under pose uncertainty using tactile feedback
Autonomous Robots
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This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labelled synthetic images. We evaluate and compare the performance of linear and non-linear classifiers. Our results show that a combination of a descriptor based on shape context with a non-linear classification algorithm leads to a stable detection of grasping points for a variety of objects.