Terrain‐aware path planning via semantic segmentation and uncertainty rejection filter with adversarial noise for mobile robots
Kangneoung Lee,
Kiju Lee
Abstract:In ground mobile robots, effective path planning relies on their ability to assess the types and conditions of the surrounding terrains. Neural network‐based methods, which primarily use visual images for terrain classification, are commonly employed for this purpose. However, the reliability of these models can vary due to inherent discrepancies between the training images and the actual environment, leading to erroneous classifications and operational failures. Retraining models with additional images from t… Show more
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