Conference Paper

Control of sensory perception for discrete event systems

Inf. Tech. & Control Syst. Div., ABB Corp. Res., Oslo, Norway
DOI: 10.1109/ICSMC.1998.725508 Conference: Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on, Volume: 1
Source: IEEE Xplore


In this paper we address the problem of controlling sensory perception for use in discrete event feedback control systems. The process of controlling sensory perception has two main objectives: 1) to collect perceptual information to identify events with high levels of confidence and 2) to keep the sensing costs low. Several event recognition techniques have been developed by the authors, where each of the event recognisers produces confidence levels of recognised events. For a discrete event control system running in normal operation, the confidence levels are typically large and only a few event recognisers are needed. Then, as the event recognition becomes harder, the confidence levels will decrease and additional event recognisers are utilised by a sensory perception controller (SPC). Hence, the overall system has the ability to actively control the use of sensory input and perception to achieve high performance discrete event recognition. Two applications are presented in the paper: 1) robotic assembly and 2) mobile navigation. Both applications fit well in the discrete event framework and demonstrate the benefits of sensory perception control.

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    ABSTRACT: We discuss the relationship between a sensory perception controller and traditional data fusion techniques. The perception controller selects process monitors in real-time, based on the expected uncertainty and cost. We experimentally compare its operation to traditional data fusion methods and show how to combine the two for improved performance
    Robotics and Automation, 1999. Proceedings. 1999 IEEE International Conference on; 02/1999
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    ABSTRACT: Soft computing has aroused vast interests among the robotics community in which intelligent control for robot is targeted. Examples of soft computing including neural networks, genetic algorithms and fuzzy logic are widely applied in the field of robotic assembly, which is widely recognized as a complicated task in robotics. In order to achieve an intelligent robot, three issues should be considered in conjunction, namely, hardware design and robot model (fundamental), control algorithm (intermediate) and system integration (advanced). Hardware design involves motor, actuator and sensor designs as well as the design of an efficient computational architecture. Algorithmic implementation requires feedback control algorithms such as position, force and hybrid control to assist a robot to accomplish a task as accurate as possible. Finally, system integration, consisting of architecture and modeling, aims at integrating hardware, robot models and control algorithm designs efficiently and effectively to accomplish specific tasks intelligently and successfully. The paper starts with an overview of the intrinsic interrelationships between hardware design and robot modeling, control algorithm, and system integration for building an intelligent robotic system. A brief outline of the hardware design and robot model is given whereas control algorithms and system integration will be focused and discussed in some depth in this paper. It is noted that hardware design and robot model are mostly viewed as the first step of intelligent system. The principal theme of this paper is to introduce the use of hidden Markov models (HMMs) to act as state recognizers, which is the key component of the intelligent robotic assembly system. The state information is eventually sent to the control strategy generator (CSG), another major component of the proposed system, in which soft computing techniques are proposed as decision-makers to determine appropriate motion strategies based on these state information. The paper concludes with the proposal of a hierarchical intelligent framework that integrates the HMM-based state recognizer and control strategy generator. This framework is structured such that it forms a generic robotic system that has the remarkable feature of easily extensible to any other types of robot.
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    ABSTRACT: Recent applications of robots for industrial automation have shown significant improvement in manufacturing processes in terms of reducing labor participation, enhancing flexibility, efficiency and quality of the products. However, most applications are limited to point-to-point and noninteractive operations in which the availability of a highly structured setup is a prerequisite. This prompts the vast emergency of researches on intelligent robotics that are aimed to improve the adaptability, flexibility and dexterity so as to enhance the intelligence of industrial robots. This paper investigates the designs of intelligent robotic systems and discusses the proposed criteria required to achieve an intelligent robotic system. A proposed conceptual framework for robotic assembly is then presented that contains two main parts, namely, a robotic state recognizer and a control strategy generator. In addition to these two components, the integration of compliant motion control into the framework will be described. An example of using the proposed framework to develop a robotic assembly system is given
    Systems, Man, and Cybernetics, 2000 IEEE International Conference on; 02/2000

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