Trajectory planning

Abstract

In this chapter, trajectory planning for robots with rigid bodies is presented. In recent years, the trend of trajectory planning is changing from manual or semi automation to full automation, because robot developers obtained much more computational resource. This trend will continue at least several decades. In recent researches, "the computational efficiency of the methods" and "the precision and quality of the solutions" are much improved by new algorithms. This fact enlarged the future landscape of this research area. From these algorithms, this chapter introduces corresponding ones, randomized kinodynamic planning (RKP), rapid semioptimal motion planning (RASMO), and linear prediction based uniform state sampling (LPUSS). These algorithms provide the trajectory solutions between initial and goal states of rigid body systems. Some of them optimizes the trajectory simultaneously with the planning. Finally, this chapter shows the potential applications of these algorithms with theoretical backgrounds.