Model-based path planning

Abstract

Model-based path planning for autonomous vehicles may incorporate knowledge of the dynamics, the environment, the planning objective, and available resources. In this chapter, we first review the most commonly used dynamic models for autonomous ground, surface, underwater, and air vehicles. We then discuss five common approaches to path planning—optimal control, level set methods, coarse planning with path smoothing, motion primitives, and random sampling—along with a qualitative comparison. The chapter includes a brief interlude on optimal path planning for kinematic car models. The aim of this chapter is to provide a high-level introduction to the field and to suggest relevant topics for further reading.