A Framework For Optimal Path Planning And Nonlinear Guidance For Autonomous Mobile Robots

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A Framework for Optimal Path Planning and Nonlinear Guidance for Autonomous Mobile Robots

The purpose of this research is to investigate methods and technology for enhancing autonomous capabilities for mobile robots. The measures of autonomy which are specifically covered in this dissertation pertain to a mobile robot's ability to make decisions and act, in other words guidance and control. This dissertation puts forth a framework using optimal path planning and nonlinear guidance techniques to address these matters. The path plans are synthesized using a numerical navigation function algorithm that will form its potential contour levels based on the minimum control effort of the system. Additionally, extensions of the path planning algorithm in the presence of uncertainty using modified versions of the RRT* and D* algorithms are studied. Then, an improved nonlinear model predictive control (NMPC) approach is employed to generate high-level guidance commands for the mobile robot to track a trajectory fitted along the path plan leading to the goal. A back stepping-like nonlinear guidance law is also implemented for comparison with the NMPC formulation. Furthermore, a cooperative control policy, making use of a combination of artificial potential functions (APF) and the numerical navigation function, is devised to guide multiple mobile robots in cooperative aggregation and social foraging tasks. The results of this research are verified in simulation and validated experimentally using the mobile robot testing platforms in the Aerospace Systems Laboratory at The University of Texas at Arlington.
Proceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021)

This book includes original, peer-reviewed research papers from the ICAUS 2021, which offers a unique and interesting platform for scientists, engineers and practitioners throughout the world to present and share their most recent research and innovative ideas. The aim of the ICAUS 2021 is to stimulate researchers active in the areas pertinent to intelligent unmanned systems. The topics covered include but are not limited to Unmanned Aerial/Ground/Surface/Underwater Systems, Robotic, Autonomous Control/Navigation and Positioning/ Architecture, Energy and Task Planning and Effectiveness Evaluation Technologies, Artificial Intelligence Algorithm/Bionic Technology and Its Application in Unmanned Systems. The papers showcased here share the latest findings on Unmanned Systems, Robotics, Automation, Intelligent Systems, Control Systems, Integrated Networks, Modeling and Simulation. It makes the book a valuable asset for researchers, engineers, and university students alike.