| 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
(författare)
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Grounding Emotion Appraisal in Autonomous Humanoids
- 2014
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The work presented in this dissertation investigates the problem for resource management of autonomous robots. Acting under the constraint of limited resources is a necessity for every robot which should perform tasks independent of human control. Some of the most important variables and performance criteria for adaptive behavior under resource constraints are discussed. Concepts like autonomy, self-sufficiency, energy dynamics, work utility, effort of action, and optimal task selection are defined and analyzed as the emphasis is on the resource balance in interaction with a human. The primary resource for every robot is its energy. In addition to the regulation of its “energy homeostasis”, a robot should perform its designer’s tasks with the required level of efficiency. A service robot residing in a human-centered environment should perform some social tasks like cleaning, helping elderly people or delivering goods. Maintaining a proper quality of work and, at the same time, not running out of energy represents a basic two-resource problem which was used as a test-bed scenario in the thesis. Safety is an important aspect of any human-robot interaction. Thus, a new three – resource problem (energy, work quality, safety) is presented and also used for the experimental investigations in the thesis.The main contribution of the thesis is developing an affective cognitive architecture. The architecture uses top-down ethological models of action selection. The action selection mechanisms are nested into a model of human affect based on appraisal theory of emotion. The arousal component of the architecture is grounded into electrical energy processes in the robotic body and is modulating the effort of movement. The provided arousal mechanism has an important functional role for the adaptability of the robot in the proposed two- and three resource scenarios. These investigations are part of a more general goal of grounding highlevel emotion substrates - Pleasure Arousal Dominance emotion space in homeostatic processes in humanoid robots. The development of the architecture took inspiration from several computation architectures of emotion in robotics, which are analyzed in the thesis.Sustainability of the basic cycles of the essential variables of a robotic system is chosen as a basic performance measure for validating the emotion components of the architecture and the grounding process. Several experiments are performed with two humanoid robots – iCub and NAO showing the role of task selection mechanism and arousal component of the architecture for the robot’s self-sufficiency and adaptability.
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| 3. |
- Kiryazov, Kiril, et al.
(författare)
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Modelling Embodied Appraisal in Humanoids : Grounding PAD space for Augmented Autonomy
- 2011
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Ingår i: Proceedings of the Workshop on Standards in Emotion Modeling, 2011.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- A computational emotion architecture is presented which grounds an aspect of an appraisal theoretic architecture in energy related processes. The incorporation of an energy constraint on emotional-cognitive behaviour allows greater potential for autonomous agency when implemented on a physical (NAO) robot platform. In this paper we present an algorithm that enables metabolic grounding of the arousal component of the PAD emotion space used in the architecture. We describe an exemplar problem that abstracts variables and performance criteria relevant to service robotics applications. Future work on further integration based on neurobiological grounding is discussed as well as means by which the exemplar scenario may be scaled up to more realistic service robotics based scenarios.
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| 4. |
- 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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| 5. |
- 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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| 6. |
- 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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| 7. |
- 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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| 8. |
- Li, Cai, et al.
(författare)
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Crawling Posture Learning in Humanoid Robots using a Natural-Actor-Critic CPG Architecture
- 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 Systems. - : MIT Press. ; , s. 1182-1190
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Konferensbidrag (refereegranskat)abstract
- In this article, a four-cell CPG network, exploiting sensory feedback, is proposed in order to emulate infant crawling gaits when utilized on the NAO robot. Based on the crawling model, the positive episodic natural-actor-critic architecture is applied to learn a proper posture of crawling on a simulated NAO. By transferring the learned results to the physical NAO, the transferability from simulation to physical world is discussed. Finally, a discussion pertaining to locomotion learning based on dynamic system theory is given in the conclusion.
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| 9. |
- Li, Cai, et al.
(författare)
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DMPs based CPG Actor Critic: A Method for Locomotion Learning
- 2014
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Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- In this article, a dynamic motor primitives (DMPs) based CPG-Actor-Critic is proposed to enable locomotion learning on a humanoid (the NAO robot) and a puppy robot (the ghostdog robot). In order to model two types of locomotion with one architecture, a novel application of an existing method to designa CPG architecture for learning locomotion. The method is to a) have an architectural base (4-cell CPG) and, b) have a learning component which is based on an existing method for designing DMPs. Learning locomotion here concerns gait emergence in relation to the robot’s body and prior knowledge. The focus of this article will be on two types of locomotion: crawling on ahumanoid and running on a puppy robot. On the two robots with two different morphologies, our method and architecture can make the robots learn by itself. We also compare the performance with respect to two state-of-the-art reinforcement learning algorithms with provided particular instantiations of ourDMPs-based CPG-Actor-Critic architecture. Finally, based on the analysis of the experimental results, a generic view/architecture for locomotion learning is discussed and introduced in the conclusion.
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| 10. |
- Li, Cai, et al.
(författare)
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Humanoids learning to crawl based on Natural CPG-Actor-Critic and Motor Primitives
- 2013
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Ingår i: Proceedings of IROS 2013 Workshop on Neuroscience and Robotics, Tokyo, Japan. ; , s. 7-15
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- In this article, a new CPG-Actor-Critic architecturebased on motor primitives is proposed to perform a crawlinglearning task on a humanoid (the NAO robot). Starting froman interdisciplinary explanation of the theories, we present twoinvestigations to test the important functions of the layeredCPG architecture: sensory feedback integration and whole-bodyposture control. Based on the analysis of the experimental results,a generic view/architecture for locomotion learning is discussedand introduced in the conclusion.
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