Description
Book SynopsisReal world Multi-Vehicle Motion Planning (MVMP) problems require the optimization of suitable performance measures under an array of complex and challenging constraints involving kinematics, dynamics, collision avoidance, and communication connectivity. The general MVMP problem is thus formulated as a Mathematical Programming (Optimization) problem.
This book presents a Mathematical Programming (MP) framework that captures the salient features of the general MVMP problem. To demonstrate the use of MP for the formulation and solution of MVMP problems, it examines in detail four representative works and summarizes several other related ones. Following this conceptual discussion, it provides a step-by-step demonstration of how to formulate, solve, and experimentally validate an MP problem that represents a MVMP. Finally, it discusses the advantages, technical challenges, and limitations of this framework.
As solution algorithms and their implementations in solvers continue to develop, it is anticipated that MP solution techniques will be applied to an increasing number of MVMP problems. The framework, formulations, and experimental approach presented here may serve as a guide for future MVMP research.
Table of Contents1: The Future is Bright.and Driverless 2: The Building Blocks 3: The Building Blocks 4: Formulating and Solving Multi-Vehicle Motion Planning Problems 5: Observations and Design Considerations. A Time-Optimal control of a double integrator. B Spectral Graph Theory and Graph Laplacian. C Polygonal approximations of a circle. D Approximation of an Ellipse by Two Intersecting Circles. E Loiter Circles. Acknowledgements. Notations and Acronyms. References
