An Approximation Algorithm for a Shortest Dubins Path Problem
Associate Professor Department of Mechanical Engineering Texas A \& M University College station, Texas, U.S.A, 77843；Professor Department of Electrical；Computer Engineering University of Florida Gainesville, Florida, U.S.A., 32611
The problem of finding the shortest path for a vehicle visiting a given sequence of target points subject to the motion constraints of the vehicle is an important problem that arises in several monitoring and surveillance applications involving unmanned aerial vehicles. There is currently no algorithm that can find an optimal solution to this problem. Therefore, heuristics that can find approximate solutions with guarantees on the quality of the solutions are useful. The best approximation algorithm currently available for the case when the distance between any two adjacent target points in the sequence is at least equal to twice the minimum radius of the vehicle has a guarantee of 3.04. This article provides a new approximation algorithm which improves this guarantee to 2.04. The developed algorithm is also implemented for hundreds of typical instances involving at most 30 points to corroborate the performance of the proposed approach.
An Efficient Method for Extracting the Shortest Path from the Dubins Set for Short Distances Between Initial and Final Positions
State Key Laboratory for Manufacturing Systems Engineering（制造系统工程国家重点实验室）；School of Automation Science and Engineering（自动化科学与工程学院）；Faculty of Electronic and Information Engineering（电子与信息工程学院）
Multi-AUV Kinematic Task Assignment based on Self-organizing Map Neural Network and Dubins Path Generator
College of Information Engineering, Shanghai Maritime University（上海海事大学信息工程学院）；Logistics Engineering College, Shanghai Maritime University（上海海事大学物流工程学院）；Mechanics Institute, University of Shanghai for Science and Technology（上海理工大学力学研究所）
A Novel Model for 3D Motion Planning for a Generalized Dubins Vehicle with Pitch and Yaw Rate Constraints
Department of Electrical Engineering and Computer Science, University of California, Irvine（加州大学 Irvine 分校 电气工程与计算机科学系）；Department of Mechanical Engineering, Texas A&M University（德克萨斯大学 A&M 学院 机械工程系）；DCS Corporation（DCS 公司）；Control Science Center, Air Force Research Laboratory, Wright-Patterson Air Force Base（空军研究实验室 威格伍德-帕特森空军基地 控制科学中心）
