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METAVerse: Meta-Learning Traversability Cost Map for Off-Road Navigation
To conduct a comprehensive evaluation, we collect driving data from various terrains and demonstrate that our method can obtain a global model that minimizes uncertainty.
Self-Supervised 3D Traversability Estimation with Proxy Bank Guidance
To mitigate the uncertainty, we introduce a deep metric learning-based method to incorporate unlabeled data with a few positive and negative prototypes in order to leverage the uncertainty, which jointly learns using semantic segmentation and traversability regression.
ScaTE: A Scalable Framework for Self-Supervised Traversability Estimation in Unstructured Environments
By integrating our framework with a model predictive controller, we demonstrate that estimated traversability results in effective navigation that enables distinct maneuvers based on the driving characteristics of the vehicles.
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