An Analysis for a Novel Path Planning Method

摘要

The aim of disseminating this research article is to introduce a novel path planner method in detail and argue that it performs as well as other offline path planners in terms of analyzing and constructing collision-free trajectories in addition to shortest possible path from start to goal configurations. Our novel path planner is able to build optimal trajectories in terms of the shortest length as well as near miss avoidance route from the initial to the goal configuration. It allows a moving point robot to make a proper transition from its assigned goal toward a collision-free path in the reasonable time frame, successfully. As an offline path planner, our planner performs the operation of analyzing the environment on static workspaces with the fixed and known initial and the goal configurations and computing optimal trajectories, using global information about the environment. As a feature of novelty, our planner benefits of using a limited amount of global knowledge, however. This helps moving robot to allocate less system resources such as memory which leads the robot to perform the process of building optimal trajectories more efficiently. The shortest route is considered to be secure enough to enable mobile robot to maneuver among obstacles in workspace without involving any near misses. Our novel path planner is able to process any types of obstacles in terms of shapes and edges flawlessly. For instance, it can be applied on any spiral or curved obstacles successfully. This novelty feature distinguishes our offline path planner from the majority of other planners that are solely able to compute the optimal trajectories for certain obstacle shapes such as polygonal obstacles. Moreover, this paper attempts to evaluate our novel path planner algorithm abilities and skills by examining it on selected workspaces. We also assess our novel path planner through comparing it with other planners to reveal its efficiency in terms of ability to route optimal trajectories in regards to minimizing trajectory distances from initial to the goal configurations as well as the reliability and safety of the optimal processed path.