Ganesan, Krishnamurthy

This thesis describes a general three-dimensional Obstacle Avoidance approach for the Autonomous Underwater Vehicle (AUV) using a forward-looking high-frequency active sonar system. This approach takes into account obstacle distance and AUV speed to determine the vehicle's heading, depth and speed. Fuzzy logic has been used to avoid the abrupt turn of the AUV in the presence of obstacles so that the vehicle can maneuver smoothly in the underwater environment. This approach has been implemented as an important part of the overall AUV software system. Using this approach, multiple objects could be differentiated automatically by the program through analyzing the sonar returns. The current vehicle state and the path of navigation of the AUV are self-adjusted depending on the location of the obstacles that are detected. A minimum safety distance is always maintained between the AUV and any object. Extensive testing of the program has been performed using several simulated AUV on-board systems undergoing different types of missions.

The project that was created for this thesis is a Case Based Reasoning application to be used in high level software design for Siemens' Telecommunications software. Currently, design engineers search for existing subtasks in the software that are similar to subtasks in their new designs by reading documentation and consulting with other engineers. The prototype for Software Design Using Case Based Reasoning (SDUCBR) stores these subtasks in a case library and enables the design engineer to locate relevant subtasks via three different indexing techniques. This thesis addresses knowledge representation and indexing mechanisms appropriate for this application. SDUCBR is domain-dependent. Cases are stored in a relational hierarchy to facilitate analyzing the existing implementation from various perspectives. The indexing mechanisms were designed to provide the software design engineer with the flexibility of describing a problem differently based on the objective, level of granularity, and special characteristics of the subtask.

Software for Autonomous Underwater Vehicles (AUVs) is usually complex. It involves several
complicated tasks such as controller, path planner, map builder, and sensor processor.
Distributed processing is unavoidable for such a complex software system with real-time response
requirements. Once these processes are distributed over several computers, it is essential
that they have some mechanism to communicate to each other to share information.
Each process might communicate with several of the other processes. Interprocess communication
becomes an important issue. This thesis discusses the design and implementation
of a generic distributed toolkit that facilitates the development of distributed software for
AUVs. This toolkit makes the details ofinterprocess communication transparent to the programmers
involved in the AUV software development. The toolkit provides efficient direct
communication between processes and does not impose any constraints on the architecture
of the distributed software. Conventional techniques for monitoring/debugging of sequential programs are not applicable
for distributed processes. This is because the correctness of a real-time distributed program
is determined not only by its "logical" correctness but also its "timing" correctness.
Monitoring mainly comprises of observation of the system during its operation. Debugging
is mostly a graphical "post-mortem" analyses of the dumps generated by the distributed program.
This thesis also presents the design of a window based generic graphical monitoring/
debugging tool.

Case-based reasoning (CBR) is a powerful reasoning paradigm for many application domains like planning, diagnosis, classification, and decision making. Recognizing solutions of past instances which are similar to the problem in hand is the central concept of CBR. Accordingly, the main research issues in CBR are efficient indexing, retrieval, and evaluation of cases. Generalization of indices has been a major concern as it directly influences the size of casebases and the ability to recognize the right candidate cases. This dissertation work presents a novel indexing scheme--using fuzzy sets to represent case indices and fuzzy aggregation operators to evaluate case matches. The proposed scheme, REFIC (REasoning from Fuzzy Indexed Cases), provides a flexible and transparent scheme to generalize case indices leading to smaller casebases. A hierarchical aggregation of different index matches is suggested for case evaluation. Also, for continuous variable domains, it is proposed to combine the solutions of a small subset of best matching cases as opposed to the conventional approach of selecting and modifying a single best one. These schemes are demonstrated by implementing a case-based navigation planner for autonomous underwater vehicles (AUVs). This navigation planner comprises of an annotated map database, a case-based path planner, and a hybrid fuzzy-CBR based reactive navigation module. The annotated map database provides a general framework for modeling the navigational environment. Annotations attached to objects and geometrical query handling are two main features of this database. Using this system as a spatial casebase, an off-line path planning system for AUV missions is designed. The obstacle avoidance module employs CBR to dynamically select promising directions of movement and to activate a subset of navigational behaviors. This reactive navigation scheme has been found to be very robust under noisy sensor data and complex obstacle distribution patterns.