Summary of Reinforcement Learning Based Escape Route Generation in Low Visibility Environments, by Hari Srikanth
Reinforcement Learning Based Escape Route Generation in Low Visibility Environments
by Hari Srikanth
First submitted to arxiv on: 27 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Machine Learning (cs.LG); Robotics (cs.RO)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This research proposes a real-time system for determining optimal search paths for firefighters and exit paths for civilians during structure fires. The system leverages LiDAR mapping, sonar, and smoke concentration data to generate maps of the environment in low-visibility conditions. By using a RANSAC-based alignment methodology, the independent point clouds are merged into a single visibility graph, which is then labeled with danger scores based on temperature and humidity data. The authors demonstrate the effectiveness of their approach by training a Linear Function Approximation based Natural Policy Gradient RL algorithm to create safe rescue and escape routes. Two systems, savior and refugee, are developed to process the environment tensor and provide guidance for firefighters and civilians respectively. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trapped in a burning building and need to get out quickly. Researchers have created a system that can help find the safest route for both firefighters trying to rescue people and people trying to escape. The system uses special tools like lasers and sensors to create maps of the environment, even when it’s dark or smoky. It then uses this information to determine which way is safest to go. Two different systems are developed: one helps firefighters find the best route to save people, while the other helps people trapped in the building find the best way to escape. |
Keywords
» Artificial intelligence » Alignment » Temperature
