Rescue robots are typically taught to perform their tasks through a combination of programmed algorithms, machine learning, and simulation training. Engineers and researchers provide the robots with data sets that include various scenariOS they may encounter, allowing them to learn from patterns and adapt to different environments. Additionally, real-world training exercises are conducted to refine their navigation, obstacle avoidance, and object recognition capabilities. This iterative process helps improve the robot's efficiency and effectiveness in rescue operations.
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