Graduation Year

2008

Document Type

Dissertation

Degree

Ph.D.

Degree Granting Department

Industrial and Management Systems Engineering

Major Professor

Ali Yalcin, Ph.D.

Co-Major Professor

Kimon Valavanis, Ph.D.

Committee Member

Tapas Das, Ph.D.

Committee Member

Sudeep Sarkar, Ph.D.

Committee Member

Nikos Tsourveloudis, Ph.D.

Keywords

Mobile robot teams, Autonomous systems, Hybrid control, Control architecture, Supervisory control

Abstract

The use of teams of coordinated mobile robots in industrial settings such as underground mining, toxic waste cleanup and material storage and handling, is a viable and reliable approach to solving such problems that require or involve automation. In this thesis, abilities a team of mobile robots should demonstrate in order to successfully perform a mission in industrial settings are identified as a set of functional components. These components are related to navigation and obstacle avoidance, localization, task achieving behaviors and mission planning. The thesis focuses on designing and developing functional components applicable to diverse missions involving teams of mobile robots; in detail, the following are presented:

1. A navigation and obstacle avoidance technique to safely navigate the robot in an unknown environment. The technique relies on information retrieved by the robot's vision system and sonar sensors to identify and avoid surrounding obstacles.

2. A localization method based on Kalman filtering and Fuzzy logic to estimate the robot's position. The method uses information derived by multiple robot sensors such as vision system, odometer, laser range finder, GPS and IMU.

3. A target tracking and collision avoidance technique based on information derived by a vision system and a laser range finder. The technique is applicable in scenarios where an intruder is identified in the patrolling area.

4. A limited lookahead control methodology responsible for mission planning. The methodology is based on supervisory control theory and it is responsible for task allocation between the robots of the team. The control methodology considers situations where a robot may fail during operation.

The performance of each functional component has been verified through extensive experimentation in indoor and outdoor environments. As a case study, a warehouse patrolling application is considered to demonstrate the effectiveness of the mission planning component.

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