# Mobile Robot Path Planning Considering Obstacle Gap Features
## 4 Conclusions  
This paper examines the crucial issue of global path planning and stable tracking for mobile robots in extensive settings. A novel hybrid planning algorithm is proposed, merging an enhanced safe A* algorithm for global path planning with sophisticated motion planning algorithms for path tracking. This innovative approach ensures real-time navigation capabilities while markedly improving path accuracy and obstacle avoidance. The enhancement of the A* algorithm through optimized risk assessment in the cost function reduces computational load and accelerates decision-making. Furthermore, the hybrid strategy utilizes a real-time motion planning method with an adaptive window mechanism, enabling dynamic extraction and switching of critical path points as sub-targets to ensure smooth and collision-free path tracking. This combination of techniques results in significantly enhanced navigation efficiency and reliability in complex environments.  
(1) The heuristic function was constructed by the influence of the gap units extracted from the global grid map on the global path planning. And the global path generated at the gap points was optimized to reduce the redundant nodes.  
(2) The best steering angle of the robot through the obstacles was calculated by considering the position relationship between the obstacles. And the robustness and success rate of navigation were improved by adding an obstacle gap angle function to the dynamic window path evaluation function, which could change the moving direction of the mobile robots.  
(3) The robot kinematics model was introduced in the process of optimizing the global path, which ensured that the setting of each virtual sub endpoint was more in line with the motion constraints, the posture adjustment was more reasonable, and the time consumed of local path planning was shorter.  
(4) The experimental results showed that the proposed algorithm has a higher computational efficiency and faster optimization speed in the global static maps. And the effectiveness and robustness of mobile robot navigation were improved by the segmented virtual endpoint calculation methods of the dynamic window method. It was superior to the references [6; 16] in terms of safety and motion performance in simulation and the real environment.  
(5) Future work will focus on collision-free local path planning algorithms that take into account the velocity of mobile robots. And the noise and uncertainty of robots will also be taken into account precisely to create a more extensive, fast, and safe path planning algorithm.  
Conceptualization, H.W. and L.H.; methodology, H.W. and L.H.; software, S.Z.; formal analysis, S.Z.; investigation, R.B. and Y.W.; resources, H.W.; data curation, Y.W. and R.B.; writing--original draft preparation, H.W.; writing--review and editing, L.H.; visualization, S.Z.; supervision, H.W.; project administration, H.W.; funding acquisition, H.W. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Natural Science Foundation of Xinjiang Uygur Autonomous Region (2022D01C392); the Xinjiang Uygur Autonomous Region Key Research and Development Project (2022B02016-1).  
Not applicable.  
The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy concerns.  
The authors declare no conflicts of interest.