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Published at November 27SCoTT: Wireless-Aware Path Planning with Vision Language Models and Strategic Chains-of-Thought
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Released Date: November 27, 2024
Authors: Aladin Djuhera1, Vlad C. Andrei1, Amin Seffo1, Holger Boche1, Walid Saad2
Aff.: 1Technical University of Munich, Munich, Germany; 2Virginia Tech, Arlington, VA, USA

| Path 1: Across the Room | Path 2: Wall to Wall | Path 3: Extreme Case | ||
| Classical A* | Average Path Gain [norm.] | 0.34 | 0.06 | 0.10 |
| Total Path Length [m] | 7.43 | 7.07 | 2.90 | |
| Time [s] | 2.23 | 2.24 | 1.01 | |
| Naïve A* | Average Path Gain [norm.] | 0.46 | 0.31 | 0.22 |
| Total Path Length [m] | 7.77 | 9.30 | 3.83 | |
| Time [s] | 4.3 | 5.32 | 3.53 | |
| DP-WA* | Average Path Gain [norm.] | 0.75 | 0.43 | 0.69 |
| Total Path Length [m] | 9.15 | 10.21 | 9.63 | |
| Time [s] | 76.04 | 74.86 | 76.97 | |
| SCoTT | Average Path Gain [norm.] | 0.72 | 0.41 | 0.62 |
| Total Path Length [m] | 8.64 | 9.32 | 8.22 | |
| Time [s] | – | – | – | |
| SCoTT- DP-WA* | Average Path Gain [norm.] | 0.73 | 0.43 | 0.66 |
| Total Path Length [m] | 9.38 | 10.21 | 9.40 | |
| Time [s] | 30.01 | 29.17 | 33.76 |