# An Intelligent Collaborative Charging System for Open-Pit Mines
## 5 The Optimal Path Planning Method for Explosive Vehicles and Loading Robots  
An Overview of the Optimal Driving Route for Explosive Vehicles and the Optimal Hole-Finding Route Plan for Loading Robots  
The planning of the driving path of the explosive vehicle and the hole-finding route of the loading robot aim to obtain the optimal driving path for the transportation of explosives by the explosive vehicle and the optimal hole-finding route for the search, positioning, and loading of the blast hole by the loading robot by using optimization algorithms. The explosive vehicle and the loading robot work collaboratively and autonomously with the assistance of the connection device and system to complete the loading of the blast hole in the open-pit mine explosive area. The explosive vehicle can complete the loading of all blast holes in the explosion area with the least number of stops and the shortest driving route, as well as the shortest hole-finding route for the loading robot. According to the design parameters of the explosive vehicle, taking the explosive vehicle as the reference center, the coverage radius of the loading robot is R, and the rotation angle covers 360 degrees. Let us suppose, according to the blasting design scheme, that there are N blast holes in the blasting area of the open-pit mine, and the two-dimensional coordinates are known. All possible parking points for the explosive vehicle in the blasting area are M, and the two-dimensional coordinates are known. The coordinates of the position points where the explosive vehicle enters and leaves the explosive area are L in and L out. When conducting charge loading at blast holes in any blasting area of an open-pit mine, three calculation and optimization tasks need to be completed. 1. Calculate the optimal layout of the parking points for explosive vehicles and the corresponding relationship between each parking point and the charge blast holes, reduce the number of parking points, and achieve full coverage of all blast holes at the same time. 2. Calculate the shortest path taken by the explosive vehicle. Starting from the known entry point into the explosive zone, it passes through each stop point only once and leaves the known exit point from the explosive zone. 3. Calculate the shortest path for the loading robot to travel, starting from the parking point of the explosive vehicle, passing through each blast hole covered by this parking point exactly once, and finally returning to the parking point of the explosive vehicle. Optimization Methods and Steps for Obtaining the Optimal Driving Path of Explosive Vehicles and the Optimal Hole-Finding Route Plan of Loading Robots  
1. The optimal layout of the parking area for explosive vehicles 1. Data input and initialization The input data are the set of drill hole points P, the candidate set of parking points T, and the coverage radius R of the hole-finding robot. 2. Coverage calculation By calculating the Euclidean distance between each drill hole point and each parking point, the coverage relationship of each parking point is established. That is, for each parking point, the covered drill hole set Ct is determined, and the parking point and the covered drill hole set are stored using a data dictionary. 3. Optimal selection of parking spots  
The parking point optimization problem is transformed into a set coverage problem for solution. From the set of drill holes covered by all parking points, the minimum parking points when covering all drill holes are found through iterative calculation. 4. Output of the coverage relationship  
Output the optimal set of parking points T and its corresponding drill hole coverage relationship {tj:C(tj)}. (2) Calculation of the shortest path traveled by the explosive vehicle  
1. Construction graph (node set and distance matrix)  
The entry point L of the explosion area, the exit point L of the explosion area, and the set of the optimal parking points T are combined into a node set to construct a distance matrix, representing the Euclidean distance between the nodes. 2.