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- 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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| 2. |
- Li, Cai
(författare)
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Reinforcement Learning of Locomotion based on Central Pattern Generators
- 2014
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Locomotion learning for robotics is an interesting and challenging area in which the movement capabilities of animals have been deeply investigated and acquired knowledge has been transferred into modelling locomotion on robots. What modellers are required to understand is what structure can represent locomotor systems in different animals and how such animals develop various and dexterous locomotion capabilities. Notwithstanding the depth of research in the area, modelling locomotion requires a deep rethinking.In this thesis, based on the umbrella of embodied cognition, a neural-body-environment interaction is emphasised and regarded as the solution to locomotion learning/development. Central pattern generators (CPGs) are introduced in the first part (Chapter 2) to generally interpret the mechanism of locomotor systems in animals. With a deep investigation on the structure of CPGs and inspiration from human infant development, a layered CPG architecture with baseline motion generation and dynamics adaptation interfaces are proposed. In the second part, reinforcement learning (RL) is elucidated as a good method for dealing with locomotion learning from the perspectives of psychology, neuroscience and robotics (Chapter 4). Several continuous-space RL techniques (e.g. episodic natural actor critic, policy learning by weighting explorations with returns, continuous action space learning automaton are introduced for practical use (Chapter 3). With the knowledge of CPGs and RL, the architecture and concept of CPG-Actor-Critic is constructed. Finally, experimental work based on published papers is highlighted in a path of my PhD research (Chapter 5). This includes the implementation of CPGs and the learning on the NAO robot for crawling and walking. The implementation is also extended to test the generalizability to different morphologies (the ghostdog robot). The contribution of this thesis is discussed from two angles: the investigation of the CPG architecture and the implementation (Chapter 6).
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| 3. |
- 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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