# Safe Path Planning of Mobile Robot Based on Improved A* Algorithm in Complex Terrains
## 5 Conclusions and Suggestions  
This paper studies the path planning problem of mobile robot based on an improved A* algorithm in a two-dimensional complex terrain environment. The conclusions and suggestions are as follows:  
1. In light of the disadvantages of the conventional A* algorithm, an improved A* algorithm is presented in this paper for the path planning of mobile robot. A new environment modeling method is proposed in which the evaluation function of A* algorithm is improved by taking into account of the safety cost. Accordingly, the planned path can be farther away from obstacles to ensure the safety of the path. A new path smoothing method is also proposed which introduces a path evaluation mechanism into the smoothing process; this is applied to smooth the path without safety reduction. Compared to the conventional A* algorithm, although the improved A* algorithm increased the path length by 0.5% and computation time by a factor of three, it reduced the turning times and sum of turning angles by 35.7% and 73.2%, respectively. It also reduced the length of risky and dangerous paths by 69.0% and 83.3%, respectively. Compared to the improved RRT* algorithm, the improved A* algorithm increased the path length and the sum of turning angles by 1.2% and 35.8%, respectively; however, it reduced the turning times by 18.2%, and also reduced the length of risky and dangerous paths by 33.0% and 38.9%, respectively. The computation time of the improved RRT* algorithm was two orders of magnitude larger than that of the improved A* algorithm. 2. In order to solve the path planning problems in complex terrains, a complex terrain environment model, which considered flat land, grassland, mountain land, and obstacles, is established in this paper. The distance and safety cost of the evaluation function of the A* algorithm were converted into time cost so that the units could be unified and their physical meanings clarified. Compared to the ACO algorithm, although the path length was increased by 1.7%, the improved A* algorithm reduced the turning times by 41.2%, reduced the sum of turning angles by 80.3%, reduced the length of risky and dangerous paths by 67.5% and 96.3% respectively, reduced the \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter** & **ACO** & **Conventional A* & **Improved RRT* & **Improved A* \\ \hline Path length (m) & 141.89 & 141.89 & 144.72 & 144.29 \\ Turning times (times) & 17 & 22 & 11 & 10 \\ Sum of turning angles (degree) & 765.00 & 990.00 & 193.84 & 150.92 \\ Length of risky path (m) & 86.88 & 85.78 & 14.71 & 28.25 \\ Length of dangerous path (m) & 57.18 & 56.32 & 0.49 & 2.10 \\ Computation time (s) & 2.18 & 0.16 & 47.39 & 0.64 \\ Movement time (s) & 127.23 & 127.54 & 81.30 & 79.56 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Performance comparison of the four algorithms in complex terrain environment. computation time by 70.6%, and it eventually led to a 37.5% fall in the movement time of the robot. Compared to the conventional A* algorithm, the improved A* algorithm increased the path length by 1.7% and increased the computation time by a factor of three; however, it reduced the turning times by 54.5%, reduced the sum of turning angles by 84.8%, reduced the length of risky and dangerous paths by 67.1% and 96.3% respectively, and it eventually led to a 37.6% fall in the movement time of the robot. Compared to the improved RRT* algorithm, the improved A* algorithm increased the length of risky and dangerous paths by 92.0% and 3.3 times respectively; however, it reduced the path length by 0.3%, reduced the turning times by 9.1%, reduced the sum of turning angles by 22.1%, reduced the movement time by 2.1%, and more importantly, the computation time dropped in two orders of magnitude. 3. Compared to the conventional A* algorithm, the improved A* algorithm achieved remarkable results and was more suitable for the path planning of mobile robots.