The appearance on the market of entertainment robots for children and families has ipso facto created the new category of motivation-basedrobots. A taxonomy of the architectures of different robot categories is propo...
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The appearance on the market of entertainment robots for children and families has ipso facto created the new category of motivation-basedrobots. A taxonomy of the architectures of different robot categories is proposed. The architecture of motivation-basedrobots is phylogenetic and ontogenetic. A tentative architecture for a specific experimental setup is described. The results of the experiment show that a new motivation arises from the interaction between the robot and the environment. Motivation-basedrobots equipped with ontogenetic architecture might provide the foundation for a new generation of robots capable of ontogenetic development. (c) 2004 Elsevier B.V. All rights reserved.
This paper describes our work to discover if LEGO Mindstorms can produce the behaviours needed for the Intelligent Sensing and Control (ISC) practical. Two robots will be built: one using straight Mindstorms and one u...
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ISBN:
(纸本)0780385608
This paper describes our work to discover if LEGO Mindstorms can produce the behaviours needed for the Intelligent Sensing and Control (ISC) practical. Two robots will be built: one using straight Mindstorms and one using Technic. These two robots will be built using similar hardware and software design. The aim is to make them as identical as possible so that direct comparison can be made. Additionally, another Mindstorms robot will be built, but enhanced to use two RCXs which can communicate each other. All three robots then are to be competed each other in robot rugby game. Their performance in the game then is used to evaluate whether Mindstorms is suitable for ISC practical.
This paper presents a Genetic Algorithm (GA) approach to evolving robot behaviours. We use fuzzy logic controllers (FLCs) to design robot behaviours. The antecedents of the FLCs are pre-designed, while their consequen...
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ISBN:
(纸本)0780378660
This paper presents a Genetic Algorithm (GA) approach to evolving robot behaviours. We use fuzzy logic controllers (FLCs) to design robot behaviours. The antecedents of the FLCs are pre-designed, while their consequences are learned using a GA. The Sony quadruped robots are used to evaluate proposed approaches in the robotic football domain. Two behaviours, ball-chasing and position-reaching, are studied and implemented. An embodied evolution scheme is adopted, by which the robot autonomously evolves its behaviours based on a layered control architecture. The results show that the robot behaviours can be automatically acquired through the GA-based learning of FLCs.
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