# Multi-Robot Exploration Based on Multi-Objective Grey Wolf Optimizer
## 5 Simulation Results and Analysis
### Simulation Results
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\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Number of**} & \multicolumn{6}{c}{**Number of Iterations**} \\ \cline{2-9}  & **Waypoints** & **60** & **80** & **100** & **120** \\ \hline \multirow{9}{*}{60} & 90.17 **92.36** & 82.08 & 92.42 91.16 88.27 & 91.51 85.93 93.54 & **98.21** 95.81 95.38 \\  & 85.55 89.10 85.36 & 90.20 87.81 87.90 & 95.92 96.07 93.47 & 89.61 89.62 89.03 \\  & 86.58 85.52 90.62 & 90.72 91.97 94.03 & 92.07 92.30 10.33 & 94.26 98.02 96.59 \\  & 86.79 90.01 82.14 & 91.11 89.21 88.30 & 97.92 95.22 21.70 & 92.89 95.22 93.38 \\  & 87.78 88.84 80.00 & 93.94 88.85 93.18 & 95.30 88.28 95.76 & 96.33 91.68 94.10 \\  & 86.03 87.62 89.68 & 90.65 85.15 92.61 & 88.89 93.60 93.46 & 95.99 91.63 93.65 \\  & 81.42 88.60 92.15 & 94.39 89.23 93.05 & 92.21 90.34 92.77 & 91.60 912.92 97.20 \\  & 88.48 85.85 84.89 & 90.43 91.98 99.39 & 92.81 91.31 94.86 & 94.28 91.69 95.57 \\  & 84.16 87.64 86.61 & 93.40 94.95 95.50 & 93.50 88.89 93.83 & 95.84 92.64 95.48 \\  & 83.59 91.63 84.70 & 93.14 92.40 95.23 & **96.57** 94.61 92.46 & 94.63 97.47 97.33 \\ \hline \multirow{9}{*}{80} & 90.53 89.00 89.24 & 96.28 93.19 94.32 & 90.16 95.48 94.30 & 96.68 94.28 86.57 \\  & 90.01 90.24 89.59 & 93.73 94.72 92.70 & 90.94 96.16 86.94 & 97.28 95.38 94.13 \\  & 88.92 88.62 86.90 & 95.38 96.69 91.98 & 96.42 96.67 94.17 & **98.40** 94.95 97.86 \\  & 87.66 84.59 91.15 & 89.37 90.90 92.56 & 94.85 93.58 94.92 & 94.07 95.16 96.54 \\  & 89.38 87.89 88.41 & 92.05 93.81 92.11 & 96.61 94.65 94.66 & 96.1 94.56 94.66 & 96.1 94.56 97.52 \\  & 88.39 90.47.87 61.0 & 95.6 **97.01** 94.86 & 96.51 95.20 28.04 & 94.90 94.76 97.84 \\  & 82.78 87.21 82.00 & 95.15 94.39 90.49 & 94.89 93.81 96.76 & 96.92 95.63 94.72 \\  & 82.86 **91.21** 84.37 & 93.43 91.49 95.56 & 93.81 **96.72** 95.43 & 92.89 95.91 96.74 \\  & 89.07 89.48 84.21 & 93.47 90.93 91.19 & 92.19 95.63 93.12 & 91.48 94.67 98.01 \\  & 89.54 87.64 89.23 & 94.18 92.93 88.49 & 94.38 83.71 92.50 & 97.8 98.45 92.14 \\ \hline \multirow{9}{*}{100} & 90.12 87.49 90.16 & 95.34 89.59 93.45 & 95.11 94.45 96.69 & 97.87 97.05 95.14 \\  & 88.19 87.59 90.10 & 92.88 95.47 95.37 & 97.29 95.81 96.48 & 97.48 95.13 97.11 \\  & 89.32 92.26 88.19 & **97.58** 96.16 91.33 & 93.90 96.97 96.57 & 96.86 98.48 96.17 \\  & 88.81 87.18 89.89 & 93.93 93.17 95.23 & 96.03 94.61 97.52 & 97.07 96.51 98.17 \\  & 80.68 87.47 89.14 & 93.77 93.65 95.73 & 92.49 93.72 95.99 & 93.09 96.31 97.09 \\  & 89.01 89.29 **91.39** & 95.55 93.25 94.18 & 96.97 97.49 97.72 & 96.16 98.40 96.43 \\  & 84.98 88.36 90.95 & 94.71 95.08 92.78 & 97.27 95.42 95.84 & 97.24 96.49 96.67 \\  & 90.45 87.77 89.86 & 92.91 91.44 86.62 & 94.40 97.11 92.47 & 96.23 95.15 97.56 \\  & 88.52 86.66 88.18 & 92.31 93.42 92.71 & 94.00 93.77 95.49 & 95.75 95.89 96.38 \\  & 91.14 86.81 89.48 & 92.62 94.45 94.70 & **97.95** 95.40 97.09 & **99.03** 94.30 98.03 \\ \hline \multirow{9}{*}{150} & 91.15 92.52 92.83 & 96.26 90.48 94.41 & 98.48 98.06 98.41 & 99.06 98.94 98.96 \\  & 91.41 91.97 86.52 & 95.21 96.27 95.72 & 96.90 **98.84** 97.24 & 95.48 98.97 97.40 \\ \cline{1-1}  & 92.14 85.72 92.02 & 95.38 93.91 96.80 & 95.91 95.92 95.63 98.63 & 92.1 98.15 97.13 \\ \cline{1-1}  & 87.60 89.30 91.56 & 95.70 95.79 94.94 & 95.37 97.71 97.34 & 98.33 98.11 97.54 \\ \cline{1-1}  & 89.73 91.20 84.98 & 95.82 93.62 96.76 & 98.52 95.38 98.54 & 98.31 97.61 96.17 \\ \cline{1-1}  & 88.67 90.40 88.26 & 91.84 95.98 95.02 & 96.67 97.64 92.76 & 98.19 98.69 98.11 \\ \cline{1-1}  & 90.52 80.15 88.25 &In Table 2, it was emphasized that, for example, the maximum map coverage with a certain sequence of decisions and the constraints, 60 iterations by 60 waypoints, is 92.36%. Furthermore, the highest result among all the set of constraints used is 99.47% at the maximum allowable set of constraints. Figure 6 shows one of the simulation-runs with the constraints: 120 iterations and 150 waypoints. In the \(a\geq 1\) stage, 87.57% of the environment was explored in half of the total number of iterations (61).