Realtime motion path generation using subtargets in a changing environment

In this work an algorithm is proposed for path planning in a changing environment. The algorithm is computationally cheap and generates a sub-optimal smooth path with bounds on the allowed velocity, acceleration and jerk. It outperforms potential field algorithms regarding both convergence and optimality. Furthermore, it is able to adapt fast in a changing environment in contrast with computationally more expensive methods, such as wavefront algorithms and global optimization methods. It is applicable to both holonomic systems and a class of nonholonomic systems