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Full-Text Articles in Mechanical Engineering
Probabilistic Searching Using A Small Unmanned Aerial Vehicle, Steven R. Hansen, Timothy W. Mclain, Michael A. Goodrich
Probabilistic Searching Using A Small Unmanned Aerial Vehicle, Steven R. Hansen, Timothy W. Mclain, Michael A. Goodrich
Faculty Publications
Ground breaking concepts in optimal search theory were developed during World War II by the U.S. Navy. These concepts use an assumed detection model to calculate a detection probability rate and an optimal search allocation. Although this theory is useful in determining when and where search effort should be applied, it offers little guidance for the planning of search paths. This paper explains how search theory can be applied to path planning for an SUAV with a fixed CCD camera. Three search strategies are developed: greedy search, contour search, and composite search. In addition, the concepts of search efficiency and …
Learning Real-Time A* Path Planner For Unmanned Air Vehicle Target Sensing, Jason K. Howlett, Timothy W. Mclain, Michael A. Goodrich
Learning Real-Time A* Path Planner For Unmanned Air Vehicle Target Sensing, Jason K. Howlett, Timothy W. Mclain, Michael A. Goodrich
Faculty Publications
This paper presents a path planner for sensing closely-spaced targets from a fixed-wing unmanned air vehicle (UAV) having a specified sensor footprint. The planner is based on the learning real-time A* (LRTA*) search algorithm and produces dynamically feasible paths that accomplish the sensing objectives in the shortest possible distance. A tree of candidate paths that span the area of interest is created by assembling primitive turn and straight sections of a specified step size in a sequential fashion from the starting position of the UAV. An LRTA* search of the tree produces feasible paths any time during its execution and …
Autonomous Vehicle Technologies For Small Fixed-Wing Uavs, Randal Beard, Derek Kingston, Morgan Quigley, Deryl Snyder, Reed Christiansen, Walt Johnson, Timothy Mclain, Michael A. Goodrich
Autonomous Vehicle Technologies For Small Fixed-Wing Uavs, Randal Beard, Derek Kingston, Morgan Quigley, Deryl Snyder, Reed Christiansen, Walt Johnson, Timothy Mclain, Michael A. Goodrich
Faculty Publications
The objective of this paper is to describe the design and implementation of a small semi-autonomous fixed-wing unmanned air vehicle. In particular we describe the hardware and software architectures used in the design. We also describe a low weight, low cost autopilot developed at Brigham Young University and the algorithms associated with the autopilot. Novel PDA and voice interfaces to the UAV are described. In addition, we overview our approach to real-time path planning, trajectory generation, and trajectory tracking. The paper is augmented with movie files that demonstrate the functionality of the UAV and its control software.
Learning Real-Time A* Path Planner For Sensing Closely-Spaced Targets From An Aircraft, Jason K. Howlett, Michael A. Goodrich, Timothy W. Mclain
Learning Real-Time A* Path Planner For Sensing Closely-Spaced Targets From An Aircraft, Jason K. Howlett, Michael A. Goodrich, Timothy W. Mclain
Faculty Publications
This work develops an any-time path planner, based on the learning real-time A* (LRTA*) search, for generating flyable paths that allow an aircraft with a specified sensor footprint to sense a group of closely-spaced targets. The LRTA* algorithm searches a tree of flyable paths for the branch that accomplishes the desired objectives in the shortest distance. The tree of paths is created by assembling primitive turn and straight sections of a specified step size. The operating parameters for the LRTA* search directly influence the running time and path-length performance of the search. A modified LRTA* search is presented that terminates …