Intrinsically Motivated Affordance Discovery and Modeling

Hart, Stephen; Grupen, Roderic A.

doi:10.1007/978-3-642-32375-1_12

Cited by 30 publications

(20 citation statements)

References 19 publications

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“…Other relevant work includes that of Grupen and colleagues who were amongst the first to recognize the potential of the cephalocaudal progression of infant development as a robotic technique (Coelho et al, 2001; Grupen, 2005; Hart and Grupen, 2013), and the proximo-distal heuristic has been widely recognized, e.g., Elman (1993). Other key projects are investigating periods of cognitive growth through a variety of robotic platforms and models (Asada et al, 2009; Mori and Kuniyoshi, 2010), and reaching has received particular attention regarding the staged release of constraints (Savastano and Nolfi, 2012), their impact (Ramırez-Contla et al, 2012), and possible emergence (Stulp and Oudeyer, 2012).…”

Section: Discussionmentioning

confidence: 99%

A psychology based approach for longitudinal development in cognitive robotics

et al. 2014

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A major challenge in robotics is the ability to learn, from novel experiences, new behavior that is useful for achieving new goals and skills. Autonomous systems must be able to learn solely through the environment, thus ruling out a priori task knowledge, tuning, extensive training, or other forms of pre-programming. Learning must also be cumulative and incremental, as complex skills are built on top of primitive skills. Additionally, it must be driven by intrinsic motivation because formative experience is gained through autonomous activity, even in the absence of extrinsic goals or tasks. This paper presents an approach to these issues through robotic implementations inspired by the learning behavior of human infants. We describe an approach to developmental learning and present results from a demonstration of longitudinal development on an iCub humanoid robot. The results cover the rapid emergence of staged behavior, the role of constraints in development, the effect of bootstrapping between stages, and the use of a schema memory of experiential fragments in learning new skills. The context is a longitudinal experiment in which the robot advanced from uncontrolled motor babbling to skilled hand/eye integrated reaching and basic manipulation of objects. This approach offers promise for further fast and effective sensory-motor learning techniques for robotic learning.

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Section: Discussionmentioning

confidence: 99%

A psychology based approach for longitudinal development in cognitive robotics

et al. 2014

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“…The OAC concept attaches the performed actions to the objects as attributes. This approach is therefore related to the affordance principle [3], which especially in the recent years has had increasing influence in robotics [4]. Take, for example, a cup, which is an entity for filling and drinking.…”

Section: Introductionmentioning

confidence: 99%

Categorizing object-action relations from semantic scene graphs

Aksoy

Abramov

Wörgötter

et al. 2010

2010 IEEE International Conference on Robotics and Automation

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Abstract-In this work we introduce a novel approach for detecting spatiotemporal object-action relations, leading to both, action recognition and object categorization. Semantic scene graphs are extracted from image sequences and used to find the characteristic main graphs of the action sequence via an exact graph-matching technique, thus providing an event table of the action scene, which allows extracting objectaction relations. The method is applied to several artificial and real action scenes containing limited context. The central novelty of this approach is that it is model free and needs a priori representation neither for objects nor actions. Essentially actions are recognized without requiring prior object knowledge and objects are categorized solely based on their exhibited role within an action sequence. Thus, this approach is grounded in the affordance principle, which has recently attracted much attention in robotics and provides a way forward for trial and error learning of object-action relations through repeated experimentation. It may therefore be useful for recognition and categorization tasks for example in imitation learning in developmental and cognitive robotics.

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“…• Patterns of Development: Infant development follows cephalocaudal and proximal to distal patterns, with eye and head control appearing before arm and torso [23]. Furthermore, upper arm control appears before forearm control and grasp learning [24], and this sequencing of activity has important ramifications for robot learning [25], [26], [27]. • Coarse to Fine Development: Infant abilities initially appear quite crude and coarse, but are gradually refined over time [28].…”

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confidence: 99%

From Saccades to Grasping: A Model of Coordinated Reaching Through Simulated Development on a Humanoid Robot

Law

Shaw

Lee

et al. 2014

IEEE Trans. Auton. Mental Dev.

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Law, J. A., Shaw, P. H., Lee, M. H., Sheldon, M. T. (2014). From Saccades to Grasping: A Model of Coordinated Reaching Through Simulated Development on a Humanoid Robot. IEEE Transactions on Autonomous Mental Development, 6 (2), 93-109Infants demonstrate remarkable talents in learning to control their sensory and motor systems. In particular the ability to reach to objects using visual feedback requires overcoming several issues related to coordination, spatial transformations, redundancy, and complex learning spaces. This paper describes a model of longitudinal development that covers the full sequence from blind motor babbling to successful grasping of seen objects. This includes the learning of saccade control, gaze control, torso control, and visually elicited reaching and grasping in 3D space. The paper builds on and extends our prior investigations into the development of gaze control, eye-hand coordination, the use of constraints to shape learning, and a schema memory system for the learning of sensorimotor experience. New contributions include our application of the LWPR algorithm to learn how movements of the torso affect the robot?s representation of space, and the first use of the schema framework to enable grasping and interaction with objects. The results from our integration of these various components into an implementation of longitudinal development on an iCub robot show their ability to generate infant-like development, from a start point with zero coordination up to skilled spatial reaching in less than 3 hours.authorsversionPeer reviewe

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Intrinsically Motivated Affordance Discovery and Modeling

Cited by 30 publications

References 19 publications

A psychology based approach for longitudinal development in cognitive robotics

A psychology based approach for longitudinal development in cognitive robotics

Categorizing object-action relations from semantic scene graphs

From Saccades to Grasping: A Model of Coordinated Reaching Through Simulated Development on a Humanoid Robot

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