Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Momentum transfer continuum between preshape and grasping based on fluidics
Download
index.pdf
Date
2012
Author
Özyer, Barış
Metadata
Show full item record
Item Usage Stats
243
views
213
downloads
Cite This
This dissertation propose a new fluidics based framework to determine a continuum between preshaping and grasping so as to appropriately preshape a multi-fingered robot hand for creating an optimal initialization of grasp. The continuum of a hand preshape closing upon an object that creates an initial object motion tendency of the object based on the impact moment patterns generated from the fingers is presented. These motion tendencies should then be suitable for the proper initiation of the grasping task. The aim is motivated by human like behavior where we preshape and land on an object to initiate a certain grasping behavior without losing the continuum during the "preshaping to grasping" phases. The continuity of momentum transfer phenomena is inspired by fluid dynamics that deals with fluid flow. We have adapted governing equations based on the physical principles of the fluid flow to generate momentum transfer from the robotic fingers, closing upon the object surface to fluid medium particles then from these fluid medium particles to the grasping object. Smoothed Particular Hydrodynamics (SPH) which is a mesh free particle method and finite volume approximation is used to analyze fluid flow equations. The fingers of the robotic hand and object are modeled by solidified fluid elements and also can be compliance. For evaluating the optimal grasp initialization of different hand preshape, we propose a decision support system consisting of artificial feed forward neural network based on the moment distribution on the object determines either : 1) given initial position and orientation of a robot hand, what preshape is suitable for generating a desired moment distribution on the surface of a given object in order to trigger a desired rotation in a desired direction when approaching with this preshaped hand or 2) given a predetermined hand preshape what initial position, orientation and hand aperture are suitable to generate a desired rotation upon approach and without causing the retroceeding of the object.
Subject Keywords
Artificial hands.
,
Robots
,
Robots
,
Robots
,
Evolutionary robotics.
,
Computational fluid dynamics
URI
http://etd.lib.metu.edu.tr/upload/12615138/index.pdf
https://hdl.handle.net/11511/22055
Collections
Graduate School of Natural and Applied Sciences, Thesis
Suggestions
OpenMETU
Core
Robotic system design for reshaping estimated human intention in human-robot interactions
Durdu, Akif; Erkmen, İsmet; Erkmen, Aydan Müşerref; Department of Electrical and Electronics Engineering (2012)
This thesis outlines the methodology and experiments associated with the reshaping of human intention via based on the robot movements in Human-Robot Interactions (HRI). Although works on estimating human intentions are quite well known research areas in the literature, reshaping intentions through interactions is a new significant branching in the field of human-robot interaction. In this thesis, we analyze how previously estimated human intentions change based on his/her actions by cooperating with mobile...
Implementation of a closed-loop action generation system on a humanoid robot through learning by demonstration
Tunaoğlu, Doruk; Şahin, Erol; Department of Computer Engineering (2010)
In this thesis the action learning and generation problem on a humanoid robot is studied. Our aim is to realize action learning, generation and recognition in one system and our inspiration source is the mirror neuron hypothesis which suggests that action learning, generation and recognition share the same neural circuitry. Dynamic Movement Primitives, an efficient action learning and generation approach, are modified in order to fulfill this aim. The system we developed (1) can learn from multiple demonstr...
Hierarchical behavior categorization using correlation based adaptive resonance theory
Yavaş, Mustafa; Alpaslan, Ferda Nur; Department of Computer Engineering (2011)
This thesis introduces a novel behavior categorization model that can be used for behavior recognition and learning. Correlation Based Adaptive Resonance Theory (CobART) network, which is a kind of self organizing and unsupervised competitive neural network, is developed for this purpose. CobART uses correlation analysis methods for category matching. It has modular and simple architecture. It can be adapted to different categorization tasks by changing the correlation analysis methods used when needed. Cob...
Equivalent linearization of 2-way fuzzy adaptive system under nonparametric uncertainty and inconsistency
Gurkan, E; Banks, SP; Erkmen, Aydan Müşerref; Erkmen, İsmet (2002-09-18)
Our aim in this paper is to design a 2-way fuzzy adaptive controller for a flexible robot arm and to analyze the stability of this controller using describing function technique. The 2-way fuzzy adaptive system is used in order to model the nonparametric uncertainties and inconsistencies present in the nonlinear system. The use of intuitionistic fuzzy sets in the 2-way fuzzy adaptive structure makes it possible to model such uncertainties. The proposed architecture is used as a controller for a flexible-joi...
A Conditional coverage path planning method for an autonomous lawn mower
Karol, Ardıç; Konukseven, Erhan İlhan; Koku, Ahmet Buğra; Department of Mechanical Engineering (2016)
Randomized and deterministic coverage path planning methods are widely used in autonomous lawn mowers. Random planning cannot guarantee a complete coverage, whereas, many deterministic techniques are not solely eligible for unstructured outdoor environments, since they highly suffer from wheel slippage or numerical drift. Besides, complete coverage techniques either demands high computational power or expensive sensor hardware. A genuine, Conditional Coverage Path Planning (CCPP) method, which satisfies com...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. Özyer, “Momentum transfer continuum between preshape and grasping based on fluidics,” Ph.D. - Doctoral Program, Middle East Technical University, 2012.