Title: Multi-Objective Path Planning Principal Investigator:

Scientific Summary: All of the classical path planning approaches such as road map, decomposing, potential fields, have own advantages and disadvantages, but generally they have a common weakness: they take into account only a single goal of PP. Most of these methods focus on the length of the path and consider the ‘shortest path ’ (a path which has minimum length between source and destination points) as the optimal path. Other methods search a ‘safe path ’ (a path with maximum distance from obstacles), or a ‘smooth path ’ (a differentiable path studied in the continuous space). While in real applications the optimal path is a combination of all of these terms. This discussion was introduced as ‘natural-looking path ’ in the study of Wein [1] where two objects, VG and VD, are combined and a new object called Visibility Voronoi diagram was extracted. Constructing visibility Voronoi diagram is very complicated in higher dimensions; especially it has an exponential complexity with respect to the space’s dimension. Also, some studies like [2, 3] tried to achieve the safety goal using Minkowski sum, or to achieve smoothness goal using a post-process on the output of sample-based methods. Unfortunately, none of these techniques don’t guarantee the optimality terms after post-processing. Furthermore, they are inefficient in the higher dimensions, clutter and corridor spaces [1]. In general, there are few studies in PP literature which take into account all optimality’s aspects simultaneously such as [4]. This method provided a single objective optimization based on the linear combination of all objectives. However, thi