Behavior-based Robot Control Using Fuzzy Discrete Event System

Abstract

The key issue associated with behavior-based architecture is the development of a behavior coordinator. A behavior coordinator should possess a number of important properties. The literature suggests that (a) both behavior arbitration and command fusion techniques should be combined in order to coordinate competitive and cooperative behaviors, (b) the coordinator should possess adequate means of modeling the current state of the world, (c) sensory uncertainties should be modeled using multivalued logic, (d) the coordinator should be capable of making persistent behavior selection, (e) it should provide the opportunity to accommodate hierarchical decisionmaking for reactive action generation, (f) it should possess predictive decision-making capability for handling future environmental uncertainties, (g) it should provide satisfactory means of decision analysis, and finally (h) it should be modular to achieve robustness with a larger number of behaviors. This thesis attempts to address some of the issues mentioned above while exploiting fuzzy logic (FL) based methodologies for behavior coordination.The initial investigation includes experimentation of different methodologies in the literature. A FL-based controller is designed for motor schema based mobile robot navigation. Fuzzy meta rules have been used to adaptively generate weights for each motor schema. It uses human reasoning to model the deterministic uncertainty of sensory data, which in turn helps to reduce the possibility of generating incorrect weights for motor schemas. Experimental results demonstrate that the fuzzy logic based approach overcomes some of the common problems of schema-based navigation.It has been observed that a pure FL-based method has several disadvantages, such as it imposes a scalability problem when the system consists of both competitive and cooperative behaviors and it does not provide any feedback measures for decision analysis. Moreover, the rule-based knowledge representation becomes complex in cases where previous state information is incorporated for persistent decision-making.While understanding the shortcomings of each technique, this thesis present a novel behavior coordination architecture using Fuzzy Discrete Event System (FDES).This architecture addresses the shortcomings of the FL-based technique using complimentary properties of Discrete Event System (DES). The DES-based method provides supervisory control techniques for behavior arbitration and has a suitable framework for decision analysis in terms of observability and controllability. Furthermore, it supports multi-level behavioral decomposition and uses previous state information of the system for persistent decision-making. As a result, the combination of FL and DES provides the opportunity to integrate several key features to achieve a high performance behavior coordinator.Finally the proposed architecture is experimentally tested using three different robotic applications, namely robotic navigation, robotic box pulling and robotic visual attention. Th...

Unified Behavior Framework for Reactive Robot Control

“…This research focuses on refining connections between the behavior based system and other components such as the deliberator. Extensions include adding stochasticity to the deliberator [31,3], temporal components [25], and alternative fuzzy representations [21]. Additionally, behavior based systems have seen application in games [19] and on airborne platforms [13].…”