Recent progress in trajectory smoothing of mobile robots

Abstract

The mobile robotics is growing rapidly and is being used in a variety of applications, greatly improving productivity. Path planning is a central part of autonomous navigation for mobile robots. However, most paths generated by these methods have sharp turns, which are unacceptable for mobile robots due to their own motion limitations or specific task scenarios. Smoother paths are therefore needed to improve the reliability and efficiency of the robot while adapting to realistic scenarios. This paper summarizes the classical curve smoothing algorithms and relate new research results presented in recent years, and divide them into six categories: polynomial interpolation, non-uniformly interpolated curves, Beizer curves, B spline curves, Reeds-Shepp curves, geometric algorithms, etc. Besides, a brief mathematical description is given along with the algorithms, and some of the algorithms are also given as examples for reference. In the future, better curve smoothing algorithms to satisfy the kinematic laws of different vehicles (robots/ships/UAVs) in multiple environments and non-simple interpolation smoothing algorithms will be proposed.