5,190 research outputs found
BEHAVIOR BASED CONTROL AND FUZZY Q-LEARNING FOR AUTONOMOUS FIVE LEGS ROBOT NAVIGATION
This paper presents collaboration of behavior based control and fuzzy Q-learning for five legs robot navigation systems. There are many fuzzy Q-learning algorithms that have been proposed to yield individual behavior like obstacle avoidance, find target and so on. However, for complicated tasks, it is needed to combine all behaviors in one control schema using behavior based control. Based this fact, this paper proposes a control schema that incorporate fuzzy q-learning in behavior based schema to overcome complicated tasks in navigation systems of autonomous five legs robot. In the proposed schema, there are two behaviors which is learned by fuzzy q-learning. Other behaviors is constructed in design step. All behaviors are coordinated by hierarchical hybrid coordination node. Simulation results demonstrate that the robot with proposed schema is able to learn the right policy, to avoid obstacle and to find the target. However, Fuzzy q-learning failed to give right policy for the robot to avoid collision in the corner location. Keywords : behavior based control, fuzzy q-learnin
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An agent-based fuzzy cognitive map approach to the strategic marketing planning for industrial firms
This is the post-print version of the final paper published in Industrial Marketing Management. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2013 Elsevier B.V.Industrial marketing planning is a typical example of an unstructured decision making problem due to the large number of variables to consider and the uncertainty imposed on those variables. Although abundant studies identified barriers and facilitators of effective industrial marketing planning in practice, the literature still lacks practical tools and methods that marketing managers can use for the task. This paper applies fuzzy cognitive maps (FCM) to industrial marketing planning. In particular, agent based inference method is proposed to overcome dynamic relationships, time lags, and reusability issues of FCM evaluation. MACOM simulator also is developed to help marketing managers conduct what-if scenarios to see the impacts of possible changes on the variables defined in an FCM that represents industrial marketing planning problem. The simulator is applied to an industrial marketing planning problem for a global software service company in South Korea. This study has practical implication as it supports marketing managers for industrial marketing planning that has large number of variables and their cause–effect relationships. It also contributes to FCM theory by providing an agent based method for the inference of FCM. Finally, MACOM also provides academics in the industrial marketing management discipline with a tool for developing and pre-verifying a conceptual model based on qualitative knowledge of marketing practitioners.Ministry of Education, Science and Technology (Korea
A proposal of an architecture for the coordination level of intelligent machines
The issue of obtaining a practical, structured, and detailed description of an architecture for the Coordination Level of Center for Intelligent Robotic Systems for Sapce Exploration (CIRSSE) Testbed Intelligent Controller is addressed. Previous theoretical and implementation works were the departure point for the discussion. The document is organized as follows: after this introductory section, section 2 summarizes the overall view of the Intelligent Machine (IM) as a control system, proposing a performance measure on which to base its design. Section 3 addresses with some detail implementation issues. An hierarchic petri-net with feedback-based learning capabilities is proposed. Finally, section 4 is an attempt to address the feedback problem. Feedback is used for two functions: error recovery and reinforcement learning of the correct translations for the petri-net transitions
Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics
“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”This position paper proposes that the study of embodied cognitive agents, such as humanoid robots, can advance our understanding of the cognitive development of complex sensorimotor, linguistic, and social learning skills. This in turn will benefit the design of cognitive robots capable of learning to handle and manipulate objects and tools autonomously, to cooperate and communicate with other robots and humans, and to adapt their abilities to changing internal, environmental, and social conditions. Four key areas of research challenges are discussed, specifically for the issues related to the understanding of: 1) how agents learn and represent compositional actions; 2) how agents learn and represent compositional lexica; 3) the dynamics of social interaction and learning; and 4) how compositional action and language representations are integrated to bootstrap the cognitive system. The review of specific issues and progress in these areas is then translated into a practical roadmap based on a series of milestones. These milestones provide a possible set of cognitive robotics goals and test scenarios, thus acting as a research roadmap for future work on cognitive developmental robotics.Peer reviewe
Analysis of the displacement of terrestrial mobile robots in corridors using paraconsistent annotated evidential logic e{\tau}
This article proposes an algorithm for a servo motor that controls the
movement of an autonomous terrestrial mobile robot using Paraconsistent Logic.
The design process of mechatronic systems guided the robot construction phases.
The project intends to monitor the robot through its sensors that send
positioning signals to the microcontroller. The signals are adjusted by an
embedded technology interface maintained in the concepts of Paraconsistent
Annotated Logic acting directly on the servo steering motor. The electric
signals sent to the servo motor were analyzed, and it indicates that the
algorithm paraconsistent can contribute to the increase of precision of
movements of servo motors
A layered fuzzy logic controller for nonholonomic car-like robot
A system for real time navigation of a nonholonomic car-like robot in a dynamic environment consists of two layers is described: a Sugeno-type fuzzy motion planner; and a modified proportional navigation based fuzzy controller. The system philosophy is inspired by human routing when moving between obstacles based on visual information including right and left views to identify the next step to the goal. A Sugeno-type fuzzy motion planner of four inputs one output is introduced to give a clear direction to the robot controller. The second stage is a modified proportional navigation based fuzzy controller based on the proportional navigation guidance law and able to optimize the robot's behavior in real time, i.e. to avoid stationary and moving obstacles in its local environment obeying kinematics constraints. The system has an intelligent combination of two behaviors to cope with obstacle avoidance as well as approaching a target using a proportional navigation path. The system was simulated and tested on different environments with various obstacle distributions. The simulation reveals that the system gives good results for various simple environments
Planning and Coordination in Hierarchies of Intelligent Dynamic Systems
On the basis of the known principle of interactions prediction (Mesarovic), our earlier proposed incremental coordination principle is extended over hierarchical collectives of intelligent dynamic systems (IDSs) after Gennady Osipov. Such systems admit arbitrary types of variables in their state vector and thereby allow investigating more general dynamic systems than “classical” ones defined in numerical state spaces. Using the concept of effective N-attainability (Osipov), a straightforward procedure of planning for hierarchical collectives of IDS is developed. As soon as a plan for reaching a goal state from the current one is found, effective implementation of this plan requires for coordination of IDSs taking their parts in the collective. We consider both aspects of coordination (coordinability with respect to the coordinator’s task and coordinability in relation to the global task) and infer necessary conditions of the coordinability for a locally organized hierarchy of IDSs
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