ABSTRACT
This chapter describes path- and motion planning methods and algorithms for a mobile robot. It provides description of the classical approach to path/motion planning. The chapter discusses some classical methods for robot path/motion planning are Roadmap, Cell decomposition, Potential Field and Mathematical Programming. It is possible to use artificial neural network for real-time collision-free path/motion planning in a dynamic environment in which may be, the obstacles are moving in the surroundings of the robot. An ant colony method for path planning takes the advantage of collective behaviour of ants which engage in a task of foraging from a nest to a source of food. The idea of using fuzzy logic for robot path planning can be envisioned for: modelling the uncertainty about/around the moving obstacles, taking the uncertainty of the measurements from various sensors into account and using certain rule base in the fuzzy inference system.
