# Non-Uniform Input-Based Adaptive Growing Neural Gas for Unstructured Environment Map Construction
## 4 Simulation Experiments
### Construction and Application of Environmental Map of Tunnel Section  
The real-time generation and optimization of the tunneling section trajectory in the unstructured environment is the key common problem to be solved as soon as possible to ensure the quality of the section forming and the tunneling operation. The excavation operation scene is shown in Figure 10. Firstly, according to the actual working conditions of roadway construction and the established environmental identification model, real-time environment information of the tunnel section on the excavation operation can be obtained. Secondly, aiming at high efficiency and strong safety, a multi-objective optimization model of cutting trajectory based on topology structure is established, which reasonably integrates the dynamic environment topology map and multi-objective optimization to realize real-time generation and optimization of tunnel section trajectory in an unstructured environment. The construction of the tunnel section environment map is an important prerequisite for the planning of the tunnel section trajectory. The construction of the section environment map based on the AGN-NU algorithm can improve the quality, real-time, and applicability of the tunnelling section trajectory planning, and achieve efficient and safe tunnelling goals.  
Figure 11 shows the simulation diagrams of cutting and forming trajectory planning based on section environment topology. In Figure 11, the red rectangles are the obstacles that cannot be cut, the red and green lines are the planned trajectories and the red one is the optimal trajectory. The experimental steps are as follows: (1) Based on the unstructured section environment identification model, the cutting motor voltage, cutting motor current, driving cylinder pressure, cutting arm vibration acceleration, the strokes of the lifting cylinder, and rotation cylinder are collected by sensors to obtain the normalized environmental information parameter and the horizontal and vertical coordinates of the collection point position. (2) Based on the AGNG-NU algorithm, using the obtained parameters as the input signals, the cross-section environment topology maps are constructed under the scenes of different cross-section shapes and dirt band positions. (3) Multiple optimal trajectory sets that meet the efficiency and safety conditions are obtained through multi-objective optimization (the red and green trajectories in the diagrams) [27]. (4) Considering the environmental topology of the section, the special requirements of cutting, and the characteristics of automatic control of large-mass bodies, the decision is made to obtain the red trajectory as the optimal trajectory for section forming. It should be pointed out that, in addition to the dirt band area, if the topology structure is adopted, the trajectory will have lots of small fluctuations, the change of which is negligible compared with the diameter of the cutting head and is within the controllable error range. Therefore, the traditional cutting method is still used. Based on this, a relatively close horizontal or vertical trajectory is planned according to the position of each node.  
Figure 10: Excavation operation scene.