DAISY: a distributed architecture for intelligent system

Distributed perceptual systems are endowed with different kind of sensors, from which information flows to suitable modules to perform useful elaborations for decisions making. In this paper a new distributed architecture, named "Distributed Architecture for Intelligent SYstem" (DAISY), is proposed. It is based on the concept of co-operating behavioral agents supervised by a "Central Engagement Module". This module integrates the processing of data coming from the behavioral agents with a symbolic level of representation, by the introduction of a "conceptual space" intermediate analogue representation. The DAISY project is under development; experiments on navigation and exploration for an autonomous robot are done to evaluate its performance.

[1]  Peter J. Burt,et al.  Smart sensing within a pyramid vision machine , 1988, Proc. IEEE.

[2]  Huosheng Hu,et al.  A parallel processing architecture for sensor-based control of intelligent mobile robots , 1996, Robotics Auton. Syst..

[3]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[4]  D. Tegolo,et al.  M-VIF: A machine-vision based on information fusion , 1993, 1993 Computer Architectures for Machine Perception.

[5]  Rodney A. Brooks,et al.  A Robust Layered Control Syste For A Mobile Robot , 2022 .

[6]  Evaggelos Geraniotis,et al.  Robust data fusion for multisensor detection systems , 1990, IEEE Trans. Inf. Theory.

[7]  Hassan Gomaa Configuration of distributed heterogeneous information systems , 1994, Proceedings of 2nd International Workshop on Configurable Distributed Systems.

[8]  Richard Fikes,et al.  Learning and Executing Generalized Robot Plans , 1993, Artif. Intell..

[9]  O DudaRichard,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972 .

[10]  C. Balkenius Natural intelligence in artificial creatures , 1995 .

[11]  Pattie Maes,et al.  Designing autonomous agents: Theory and practice from biology to engineering and back , 1990, Robotics Auton. Syst..

[12]  Vito Di Gesù,et al.  Local operators to detect regions of interest , 1997, Pattern Recognit. Lett..

[13]  David Chapman,et al.  What are plans for? , 1990, Robotics Auton. Syst..

[14]  Andrzej M. Goscinski,et al.  Distributed operating systems - the logical design , 1991 .

[15]  Bruce Eckel Thinking in Java , 1998 .

[16]  Gaetano Gerardi,et al.  The Programmable and Configurable Low Level Vision Unit of the HERMIA Machine , 1992, MVA.

[17]  Tim Smithers,et al.  Symbol grounding via a hybrid architecture in an autonomous assembly system , 1990, Robotics Auton. Syst..

[18]  Christopher M. Brown,et al.  Issues in selective perception , 1992, [1992] Proceedings. 11th IAPR International Conference on Pattern Recognition.

[19]  Ruzena Bajcsy,et al.  Recovery of Parametric Models from Range Images: The Case for Superquadrics with Global Deformations , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  P. Gärdenfors Three levels of inductive inference , 1995 .

[21]  Salvatore Gaglio,et al.  A Cognitive Architecture for Artificial Vision , 1997, Artif. Intell..

[22]  D. Tegolo,et al.  Visual dynamic environment for distributed systems , 1995, Proceedings of Conference on Computer Architectures for Machine Perception.

[23]  Ronald C. Arkin,et al.  Integrating behavioral, perceptual, and world knowledge in reactive navigation , 1990, Robotics Auton. Syst..

[24]  Alex Pentland,et al.  Perceptual Organization and the Representation of Natural Form , 1986, Artif. Intell..