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The research on deformation zoning mechanism of tunnel surrounding rock is of great significance for ensuring safe production and disaster prevention in coal mines. However, the traditional deformation zoning theory of tunnel surrounding rock uses the ideal strain softening model as the criterion for judging the zoning type of all tunnel surrounding rock, ignoring the difference between the deformation zoning type of a specific actual tunnel and the basic zoning type of surrounding rock. In order to study the method for determining the actual deformation zoning type of tunnel surrounding rock, the formation mechanism of the actual deformation zoning of tunnel surrounding rock has been revealed. Combined with engineering examples, a method for determining the actual deformation zoning type and boundary stress of specific tunnel surrounding rock has been proposed. The results show that the boundary stress and position of the actual deformation zone are determined by the peak strength fitting line, residual strength fitting line, support strength line, and the position of the circumferential and radial stress relationship lines of each deformation zone. The actual boundary stress of each zone of tunnel surrounding rock is ultimately only related to the basic mechanical properties of the tunnel surrounding rock and the in-situ stress field. The research results can provide reference for disaster management of underground engineering, stability evaluation of surrounding rock, and support scheme design.

The traditional A* algorithm has several problems in practical applications, such as many path turning points, redundant nodes, and long running time. it is sometimes impossible to plan the theoretical optimal route. To solve the above problem, this paper presents an optimized A* algorithm, the adaptive adjustment step algorithm and the three-time Bezier curve are used to solve the problems of many turning points, large turning angles, and long running time in the search path. Moreover, aiming at the path planning problem of mobile robots facing dynamic obstacle interference in complex environments, an algorithm that integrates the improved A* algorithm with the dynamic window method is proposed, which not only solves the shortcomings of the A* algorithm in which the dynamic obstacles cannot be avoided, but also prevents the mobile robot from falling into local optimization. The results show that the fusion algorithm of the improved A* algorithm and the dynamic window method with the traditional A* algorithm reduces the number of turns by 50% and the path length by 3.62% compared with the original algorithm. In the same environment, compared with the traditional algorithm, the hybrid algorithm in this paper reduces the average time consumption by 10.27%, the number of path inflection points by 57.14%, and the accuracy is higher than 33.33%, which is more effective in complex dynamic environments.