Introduction to path planning in three methods

All services provided by robots to humans are based on navigation control. Navigation control includes positioning and navigation. Path planning is a key part of navigation. The navigation control algorithm is at the heart of determining the behaviour of the robot. The navigation control module includes global path planning and local path planning. Global path planning is the creation of a feasible path from the start point to the target point using an existing electronic map as a standard. Local path planning, also known as local obstacle avoidance, is the process by which sensors scan for unknown obstacles during the robot's operation and redefine a local path around the obstacles towards the target point. This paper describes some of the main algorithms that are more widely used in motion planning, including sampling-based search methods such as RRT and its range of optimisation methods. Each of these methods has its own search process and results. There is also a search algorithm called the Markov decision process model, which we tried to combine with RRT but failed due to different application areas.