Proceedings ArticleDOI
Segmentation and learning of unknown objects through physical interaction
David Schiebener,Ales Ude,Jun Morimoto,Tamim Asfour,Rüdiger Dillmann +4 more
- pp 500-506
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TLDR
It is shown that the learned model, in combination with the proposed segmentation process, allows robust object recognition in cluttered scenes.Abstract:
This paper reports on a new approach for segmentation and learning of new, unknown objects with a humanoid robot. No prior knowledge about the objects or the environment is needed. The only necessary assumptions are firstly, that the object has a (partly) smooth surface that contains some distinctive visual features and secondly, that the object moves as a rigid body. The robot uses both its visual and manipulative capabilities to segment and learn unknown objects in unknown environments. The segmentation algorithm is based on pushing hypothetical objects by the robot, which provides a sufficient amount of information to distinguish the object from the background. In the case of a successful segmentation, additional features are associated with the object over several pushing-and-verification iterations. The accumulated features are used to learn the appearance of the object from multiple viewing directions. We show that the learned model, in combination with the proposed segmentation process, allows robust object recognition in cluttered scenes.read more
Citations
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Journal ArticleDOI
Data-Driven Grasp Synthesis—A Survey
TL;DR: A review of the work on data-driven grasp synthesis and the methodologies for sampling and ranking candidate grasps and an overview of the different methodologies are provided, which draw a parallel to the classical approaches that rely on analytic formulations.
Journal ArticleDOI
Interactive Perception: Leveraging Action in Perception and Perception in Action
Jeannette Bohg,Karol Hausman,Bharath Sankaran,Oliver Brock,Danica Kragic,Stefan Schaal,Gaurav S. Sukhatme +6 more
TL;DR: This survey postulates this as a principle for robot perception and collects evidence in its support by analyzing and categorizing existing work in this area, and provides an overview of the most important applications of IP.
Posted Content
A Survey of Semantic Segmentation
TL;DR: This survey gives an overview over different techniques used for pixel-level semantic segmentation such as unsupervised methods, Decision Forests and SVMs and recently published approaches with convolutional neural networks.
Proceedings ArticleDOI
Using manipulation primitives for brick sorting in clutter
Megha Gupta,Gaurav S. Sukhatme +1 more
TL;DR: A robust pipeline is presented that combines perception and manipulation to accurately sort Duplo bricks by color and size and uses two simple motion primitives to manipulate the scene in ways that help the robot to improve its perception.
Book ChapterDOI
Learning to Singulate Objects Using a Push Proposal Network
TL;DR: In this paper, a neural network-based approach that separates unknown objects in clutter by selecting favorable push actions is presented, which enables the robot to perform the task with a high success rate and a low number of required push actions.
References
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Journal ArticleDOI
Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography
TL;DR: New results are derived on the minimum number of landmarks needed to obtain a solution, and algorithms are presented for computing these minimum-landmark solutions in closed form that provide the basis for an automatic system that can solve the Location Determination Problem under difficult viewing.
Proceedings ArticleDOI
Object recognition from local scale-invariant features
TL;DR: Experimental results show that robust object recognition can be achieved in cluttered partially occluded images with a computation time of under 2 seconds.
Book
Multiple view geometry in computer vision
Richard Hartley,Andrew Zisserman +1 more
TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.
Multiple View Geometry in Computer Vision.
TL;DR: This book is referred to read because it is an inspiring book to give you more chance to get experiences and also thoughts and it will show the best book collections and completed collections.
Proceedings ArticleDOI
A Combined Corner and Edge Detector
Chris Harris,Mike Stephens +1 more
TL;DR: The problem the authors are addressing in Alvey Project MMI149 is that of using computer vision to understand the unconstrained 3D world, in which the viewed scenes will in general contain too wide a diversity of objects for topdown recognition techniques to work.