| 1. |
- Billing, Erik, 1981-, et al.
(författare)
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Finding Your Way from the Bed to the Kitchen: Reenacting and Recombining Sensorimotor Episodes Learned from Human Demonstration
- 2016
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Ingår i: Frontiers in Robotics and Ai. - Lausanne, Switzerland : Frontiers Media SA. - 2296-9144. ; 3
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Tidskriftsartikel (refereegranskat)abstract
- Several simulation theories have been proposed as an explanation for how humans and other agents internalize an "inner world" that allows them to simulate interactions with the external real world - prospectively and retrospectively. Such internal simulation of interaction with the environment has been argued to be a key mechanism behind mentalizing and planning. In the present work, we study internal simulations in a robot acting in a simulated human environment. A model of sensory-motor interactions with the environment is generated from human demonstrations and tested on a Robosoft Kompai robot. The model is used as a controller for the robot, reproducing the demonstrated behavior. Information from several different demonstrations is mixed, allowing the robot to produce novel paths through the environment, toward a goal specified by top-down contextual information. The robot model is also used in a covert mode, where the execution of actions is inhibited and perceptions are generated by a forward model. As a result, the robot generates an internal simulation of the sensory-motor interactions with the environment. Similar to the overt mode, the model is able to reproduce the demonstrated behavior as internal simulations. When experiences from several demonstrations are combined with a top-down goal signal, the system produces internal simulations of novel paths through the environment. These results can be understood as the robot imagining an "inner world" generated from previous experience, allowing it to try out different possible futures without executing actions overtly. We found that the success rate in terms of reaching the specified goal was higher during internal simulation, compared to overt action. These results are linked to a reduction in prediction errors generated during covert action. Despite the fact that the model is quite successful in terms of generating covert behavior toward specified goals, internal simulations display different temporal distributions compared to their overt counterparts. Links to human cognition and specifically mental imagery are discussed.
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| 2. |
- Kiryazov, Kiril, et al.
(författare)
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The role of arousal in embodying the cueXdeficit model in multi-resource human robot interaction
- 2013
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Ingår i: Advances in Artificial Life, ECAL 2013, Proceedings of the Twelfth European Conference on the Synthesis and Simulation of Living System. - : MIT Press. ; , s. 19-26, s. 19-26
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Konferensbidrag (refereegranskat)abstract
- In this paper is investigated the problem of managing limited resources in human-robot interaction with a computational architecture of emotion. The architecture is based on the appraisal theory of affect and an ethological motivational model of task selection. Key variables and performance criteria for robotic energy autonomous behaviour in interaction with humans are discussed. The role of arousal for modulating effort of movement is explored. It is shown that the architecture can manage task selection and the effort of the movement and offers sustainable basic-cycles in exemplar "two-resource problem" test-bed scenarios for an iCub robot. An extension of the architecture with a third "resource"—safety—is presented and how the architecture is able to solve the new "three-resource" problem is demonstrated.
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| 3. |
- Kiryazov, Kiril, et al.
(författare)
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The role of arousal in two-resource problem tasks for humanoid service robots
- 2013
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Ingår i: IEEE RO-MAN 2013. - : IEEE. - 9781479905096 ; , s. 62-69
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Konferensbidrag (refereegranskat)abstract
- A computational architecture of emotion is presented which grounds a component of an appraisal cognitive model into the homeostatic processes of a humanoid robot. The focus of the present work entails a `grounding' of the arousal component of the Pleasure Arousal Dominance emotion space into the electrical energy processes of an iCub robot. Key variables and performance criteria for robotic energy autonomous behavior in interaction with human are discussed. We show that our bio-inspired affective architecture offers viable basic cycles in exemplar “two-resource problem” testbed scenarios for a real iCub robot. The expression of the robot's emotional state and its role for the efficient interaction in the proposed two-resource problem task is discussed and experimental designs are presented.
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| 4. |
- Lee, Gauss, et al.
(författare)
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Modelling Early Infant Walking : Testing a Generic CPG Architecture on the NAO Humanoid
- 2011
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Ingår i: IEEE International Conference on Development and Learning (ICDL), 2011. - : IEEE conference proceedings. - 9781612849898 ; , s. 1-6
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Konferensbidrag (refereegranskat)abstract
- In this article, a simple CPG network is shown to model early infant walking, in particular the onset of independent walking. The difference between early infant walking and early adult walking is addressed with respect to the underlying neurophysiology and evaluated according to gait attributes. Based on this, we successfully model the early infant walking gait on the NAO robot and compare its motion dynamics and performance to those of infants. Our model is able to capture the core properties of early infant walking. We identify differences in the morphologies between the robot and infant and the effect of this on their respective performance. In conclusion, early infant walking can be seen to develop as a function of the CPG network and morphological characteristics.
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| 5. |
- Li, Cai, et al.
(författare)
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A novel approach to locomotion learning: Actor-Critic architecture using central pattern generators and dynamic motor primitives
- 2014
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Ingår i: Frontiers in Neurorobotics. - : Frontiers. - 1662-5218. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- In this article, we propose an architecture of a bio-inspired controller that addresses the problem of learning different locomotion gaits for different robot morphologies. The modeling objective is split into two: baseline motion modeling and dynamics adaptation. Baseline motion modeling aims to achieve fundamental functions of a certain type of locomotion and dynamics adaptation provides a "reshaping" function for adapting the baseline motion to desired motion. Based on this assumption, a three-layer architecture is developed using central pattern generators (CPGs, a bio-inspired locomotor center for the baseline motion) and dynamic motor primitives (DMPs, a model with universal "reshaping" functions). In this article, we use this architecture with the actor-critic algorithms for finding a good "reshaping" function. In order to demonstrate the learning power of the actor-critic based architecture, we tested it on two experiments: (1) learning to crawl on a humanoid and, (2) learning to gallop on a puppy robot. Two types of actor-critic algorithms (policy search and policy gradient) are compared in order to evaluate the advantages and disadvantages of different actor-critic based learning algorithms for different morphologies. Finally, based on the analysis of the experimental results, a generic view/architecture for locomotion learning is discussed in the conclusion.
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| 6. |
- Li, Cai, et al.
(författare)
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Humanoids learning to walk : a natural CPG-actor-critic architecture
- 2013
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Ingår i: Frontiers in Neurorobotics. - : Frontiers Media S.A.. - 1662-5218. ; 7:5
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Tidskriftsartikel (refereegranskat)abstract
- The identification of learning mechanisms for locomotion has been the subject of much research for some time but many challenges remain. Dynamic systems theory (DST) offers a novel approach to humanoid learning through environmental interaction. Reinforcement learning (RL) has offered a promising method to adaptively link the dynamic system to the environment it interacts with via a reward-based value system. In this paper, we propose a model that integrates the above perspectives and applies it to the case of a humanoid (NAO) robot learning to walk the ability of which emerges from its value-based interaction with the environment. In the model, a simplified central pattern generator (CPG) architecture inspired by neuroscientific research and DST is integrated with an actor-critic approach to RL (cpg-actor-critic). In the cpg-actor-critic architecture, least-square-temporal-difference based learning converges to the optimal solution quickly by using natural gradient learning and balancing exploration and exploitation. Futhermore, rather than using a traditional (designer-specified) reward it uses a dynamic value function as a stability indicator that adapts to the environment. The results obtained are analyzed using a novel DST-based embodied cognition approach. Learning to walk, from this perspective, is a process of integrating levels of sensorimotor activity and value.
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| 7. |
- Li, Cai, et al.
(författare)
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Humanoids that crawl : Comparing gait performance of iCub and NAO using a CPG architecture
- 2011
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Ingår i: Proceedings - 2011 IEEE International Conference on Computer Science and Automation Engineering, CSAE 2011. - : IEEE conference proceedings. - 9781424487271 - 9781424487288 - 9781424487264 - 9781424487257 ; , s. 577-582
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Konferensbidrag (refereegranskat)abstract
- In this article, a generic CPG architecture is used to model infant crawling gaits and is implemented on the NAO robot platform. The CPG architecture is chosen via a systematic approach to designing CPG networks on the basis of group theory and dynamic systems theory. The NAO robot performance is compared to the iCub robot which has a different anatomical structure. Finally, the comparison of performance and NAO whole-body stability are assessed to show the adaptive property of the CPG architecture and the extent of its ability to transfer to different robot morphologies. © 2011 IEEE.
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| 8. |
- Li, Cai, et al.
(författare)
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Modelling Walking Behaviors Based on CPGs : A Simplified Bio-inspired Architecture
- 2012
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Ingår i: From Animals to Animats 12. - Berlin; Heidelberg : Springer Berlin/Heidelberg. - 9783642330926 - 9783642330933 ; , s. 156-166
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Konferensbidrag (refereegranskat)abstract
- In this article, we use a recurrent neural network including four-cell core architecture to model the walking gait and implement it with the simulated and physical NAO robot. Meanwhile, inspired by the biological CPG models, we propose a simplified CPG model which comprises motorneurons, interneurons, sensor neurons and the simplified spinal cord. Within this model, the CPGs do not directly output trajectories to the servo motors. Instead, they only work to maintain the phase relation among ipsilateral and contralateral limbs. The final output is dependent on the integration of CPG signals, outputs of interneurons, motor neurons and sensor neurons (sensory feedback).
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| 9. |
- Montebelli, Alberto, et al.
(författare)
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Microbial fuel cell driven behavioural dynamics in robot simulations
- 2010
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Ingår i: Artificial Life XII. - Cambridge, Massachusetts : MIT Press. - 9780262290753 - 0262290758 ; , s. 749-756
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Konferensbidrag (refereegranskat)abstract
- With the present study we report the first application of a recently proposed model for realistic microbial fuel cells (MFCs) energy generation dynamics, suitable for robotic simulations with minimal and extremely limited computational overhead. A simulated agent was adapted in order to engage in a viable interaction with its environment. It achieved energy autonomy by maintaining viable levels of the critical variables of MFCs, namely cathodic hydration and anodic substrate biochemical energy. After unsupervised adaptation by genetic algorithm, these crucial variables modulate the behavioral dynamics expressed by viable robots in their interaction with the environment. The analysis of this physically rooted and self-organized dynamic action selection mechanism constitutes a novel practical contribution of this work. We also compare two different viable strategies, a self-organized continuous and a pulsed behavior, in order to foresee the possible cognitive implications of such biologicalmechatronics hybrid symbionts in a novel scenario of ecologically grounded energy and motivational autonomy.
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| 10. |
- Montebelli, Alberto
(författare)
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Modeling the Role of Energy Management in Embodied Cognition
- 2012
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The quest for adaptive and autonomous robots, flexible enough to smoothly comply with unstructured environments and operate in close interaction with humans, seems to require a deep rethinking of classical engineering methods. The adaptivity of natural organisms, whose cognitive capacities are rooted in their biological organization, is an obvious source of inspiration. While approaches that highlight the role of embodiment in both cognitive science and cognitive robotics are gathering momentum, the crucial role of internal bodily processes as foundational components of the biological mind is still largely neglected.This thesis advocates a perspective on embodiment that emphasizes the role of non-neural bodily dynamics in the constitution of cognitive processes in both natural and artificial systems. In the first part, it critically examines the theoretical positions that have influenced current theories and the author's own position. The second part presents the author's experimental work, based on the computer simulation of simple robotic agents engaged in energy-related tasks. Proto-metabolic dynamics, modeled on the basis of actual microbial fuel cells for energy generation, constitute the foundations of a powerful motivational engine. Following a history of adaptation, proto-metabolic states bias the robot towards specific subsets of behaviors, viably attuned to the current context, and facilitate a swift re-adaptation to novel tasks. Proto-metabolic dynamics put the situated nature of the agent-environment sensorimotor interaction within a perspective that is functional to the maintenance of the robot's overall `survival'. Adaptive processes tend to convert metabolic constraints into opportunities, branching into a rich and energetically viable behavioral diversity.
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