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
Goal emulation and planning in perceptual space using learned affordances
Date
2011-7
Author
Ugur, Emre
Oztop, Erhan
Şahin, Erol
Metadata
Show full item record
Item Usage Stats
177
views
0
downloads
Cite This
In this paper, we show that through self-interaction and self-observation, an anthropomorphic robot equipped with a range camera can learn object affordances and use this knowledge for planning. In the first step of learning, the robot discovers commonalities in its action-effect experiences by discovering effect categories. Once the effect categories are discovered, in the second step, affordance predictors for each behavior are obtained by learning the mapping from the object features to the effect categories. After learning, the robot can make plans to achieve desired goals, emulate end states of demonstrated actions, monitor the plan execution and take corrective actions using the perceptual structures employed or discovered during learning. We argue that the learning system proposed shares crucial elements with the development of infants of 7-10 months age, who explore the environment and learn the dynamics of the objects through goal-free exploration. In addition, we discuss goal emulation and planning in relation to older infants with no symbolic inference capability and non-linguistic animals which utilize object affordances to make action plans.
Subject Keywords
Affordance
,
Developmental robotics
,
Sensorimotor learning
,
Manipulation
,
Perception
,
Cognitive robotics
URI
https://hdl.handle.net/11511/28282
Journal
Robotics and Autonomous Systems
DOI
https://doi.org/10.1016/j.robot.2011.04.005
Collections
Department of Computer Engineering, Article
Suggestions
OpenMETU
Core
From primitive behaviors to goal-directed behavior using affordances
Doǧar, Mehmet R.; Çakmak, Maya; Uǧur, Emre; Şahin, Erol (2007-12-01)
In this paper, we studied how a mobile robot equipped with a 3D laser scanner can start from primitive behaviors and learn to use them to achieve goal-directed behaviors. For this purpose, we propose a learning scheme that is based on the concept of "affordances", where the robot first learns about the different kind of effects it can create in the environment and then links these effects with the perception of the initial environment and the executed primitive behavior. It uses these learned relations to c...
GESwarm Grammatical Evolution for the Automatic Synthesis of Collective Behaviors in Swarm Robotics
Ferrante, Eliseo; Turgut, Ali Emre; DuenezGuzman, Edgar; Wenseleers, Tom (2013-07-10)
In this paper we propose GESwarm, a novel tool that can automatically synthesize collective behaviors for swarms of autonomous robots through evolutionary robotics. Evolutionary robotics typically relies on artificial evolution for tuning the weights of an artificial neural network that is then used as individual behavior representation. The main caveat of neural networks is that they are very difficult to reverse engineer, meaning that once a suitable solution is found, it is very difficult to analyze, to ...
A developmental framework for learning affordances
Uğur, Emre; Şahin, Erol; Öztop, Erhan; Department of Computer Engineering (2010)
We propose a developmental framework that enables the robot to learn affordances through interaction with the environment in an unsupervised way and to use these affordances at different levels of robot control, ranging from reactive response to planning. Inspired from Developmental Psychology, the robot’s discovery of action possibilities is realized in two sequential phases. In the first phase, the robot that initially possesses a limited number of basic actions and reflexes discovers new behavior primiti...
Staged Development of Robot Skills: Behavior Formation, Affordance Learning and Imitation with Motionese
Ugur, Emre; Nagai, Yukie; Şahin, Erol; ÖZTOP, ERHAN (2015-06-01)
Inspired by infant development, we propose a three staged developmental framework for an anthropomorphic robot manipulator. In the first stage, the robot is initialized with a basic reach-and-enclose-on-contact movement capability, and discovers a set of behavior primitives by exploring its movement parameter space. In the next stage, the robot exercises the discovered behaviors on different objects, and learns the caused effects; effectively building a library of affordances and associated predictors. Fina...
Decoupled Cascaded PID Control of an Aerial Manipulation System
Bulut, Nebi; Turgut, Ali Emre; Arıkan, Kutluk Bilge (2019-12-01)
This paper presents the control of an aerial manipulation system with a quadrotor and a 2-DOF robotic arm. Firstly, the kinematic model of the combined system and the Denavit-Hartenberg parameters of the serial robotic arm are obtained. Then, to derive the dynamics of the system, the quadrotor and the 2-DOF robotic arm are modeled as a combined system. The Lagrange-d'Alembert formulation is used to obtain the equation of motion of the combined system. Later, decoupled controllers are developed for the gener...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
E. Ugur, E. Oztop, and E. Şahin, “Goal emulation and planning in perceptual space using learned affordances,”
Robotics and Autonomous Systems
, pp. 580–595, 2011, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/28282.