# Multitarget Search Algorithm Using Swarm Robots in an Unknown 3D Mountain Environment
## 5 Simulation Experiment and Results
Figure 6d shows the trajectory of robot \(R_{21}\) during the period from \(t=1\) to the robot swarm finding all targets. As seen from the trajectory shown in the figure, when the upward slope of the robot's movement direction is too high for it to climb, the robot will adjust its movement direction to the climbing slope according to the 3D curved obstacle tracking algorithm and move as close to the original direction as possible. Figure 5: 3D search simulation diagram. (**a**) Target search terrain, (**b**) When \(t=1\), the robot and the target are located, (**c**) When \(t=37\), a robot detects a target signal and forms a suballiance. (**d**) When \(t=1\)-\(58\), a robot searches the trajectory of target \(tar_{8}\). (**e**) When \(t=127\), the target is found. (**f**) When \(t=185\), the trajectory of the robot. (**g**) When \(t=255\), all targets have been found. (**h**) When \(t=1\)–\(255\), the trajectories of all the robots. Figure 6e shows the positions of the robots and targets at \(t=329\). All targets have been found by swarm robots at this point. Figure 6f shows the trajectories of all robots in the swarm robot target search process. The figure shows that according to the proposed method, the robots can successfully find all targets in the task area. The robots will be more inclined to move in the region with a slower slope, but they can also move in the direction with a lower slope in a region with a higher slope. \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{\(n_{u}\)} & \multicolumn{4}{c}{**Step**} & \multicolumn{4}{c}{**Energy Consumption (\(\times 10^{4}\))**} \\ \cline{2-9}  & **30** & **40** & **50** & **60** & **30** & **40** & **50** & **60** \\ \hline  & 481 & 250 & 226 & 217 & 11.494 & 8.191 & 9.109 & 10.761 \\  & 370 & 283 & 220 & 215 & 8.857 & 9.197 & 8.868 & 10.483 \\  & 332 & 343 & 271 & 211 & 8.277 & 10.653 & 10.668 & 10.429 \\  & 455 & 249 & 232 & 219 & 11.385 & 8.128 & 9.474 & 10.784 \\  & 354 & 247 & 234 & 230 & 8.729 & 7.799 & 9.483 & 11.259 \\  & 287 & 249 & 242 & 205 & 6.956 & 7.951 & 9.887 & 10.260 \\  & 356 & 267 & 253 & 216 & 8.492 & 8.515 & 10.152 & 10.685 \\  & 286 & 230 & 245 & 190 & 7.085 & 7.466 & 9.694 & 9.456 \\  & 282 & 237 & 260 & 217 & 7.008 & 7.487 & 10.235 & 10.699 \\  & 311 & 215 & 207 & 227 & 7.611 & 7.024 & 8.480 & 10.972 \\  & 367 & 297 & 235 & 209 & 9.088 & 9.579 & 9.434 & 10.453 \\  & 282 & 232 & 235 & 194 & 6.962 & 7.501 & 9.244 & 9.474 \\  & 316 & 260 & 222 & 230 & 7.767 & 8.350 & 8.954 & 11.185 \\  & 343 & 295 & 244 & 206 & 8.513 & 9.532 & 9.731 & 10.289 \\  & 272 & 277 & 225 & 200 & 6.736 & 8.732 & 8.992 & 9.941 \\  & 240 & 248 & 227 & 220 & 5.883 & 8.009 & 9.217 & 10.916 \\  & 360 & 262 & 207 & 227 & 9.011 & 8.231 & 8.460 & 11.091 \\  & 294 & 280 & 244 & 195 & 7.068 & 8.923 & 9.709 & 9.728 \\  & 379 & 299 & 230 & 216 & 9.444 & 9.568 & 9.310 & 10.643 \\  & 355 & 269 & 239 & 225 & 8.679 & 8.590 & 9.537 & 10.901 \\  & 336 & 218 & 236 & 196 & 8.364 & 6.932 & 9.666 & 9.756 \\  & 253 & 352 & 275 & 221 & 6.225 & 10.924 & 10.894 & 10.800 \\  & 358 & 255 & 203 & 175 & 8.912 & 8.152 & 8.373 & 8.802 \\  & 259 & 239 & 227 & 229 & 6.288 & 7.729 & 9.191 & 11.157 \\  & 336 & 244 & 219 & 217 & 8.295 & 7.646 & 8.863 & 10.754 \\  & 457 & 251 & 260 & 216 & 11.264 & 8.030 & 10.370 & 10.591 \\  & 328 & 259 & 243 & 190 & 8.016 & 8.419 & 9.658 & 9.565 \\  & 261 & 329 & 234 & 203 & 6.615 & 10.298 & 9.465 & 9.996 \\  & 305 & 263 & 218 & 222 & 7.376 & 8.497 & 8.877 & 11.051 \\  & 340 & 280 & 227 & 206 & 8.399 & 8.946 & 9.098 & 10.251 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Target \(n_{T}=10\) and mountain slope less than or equal to \(\beta\): the number of steps and energy consumption required for the robots to complete the task search. Taking the number of robots \(n_{u}=30,\ 40,\ 50,\ \text{or}\ 60\) and the number of targets \(n_{T}=10\), the experiment was repeated 30 times, and the following data as shown in Table 4.  
Figure 6: 3D simulation of a target search when the slope is greater than \(\beta\).