Continual Learning for Traversability Prediction with Uncertainty-Aware Adaptation

arXiv:2609.17141 · cs.RO, cs.AI, cs.LG · Submitted 2026-09-15 · Read on arXiv

cs.RO, cs.AI, cs.LG

Submitted: 2026-09-15

Updated: 2026-09-15

Comments: Accepted version of the article published in IEEE Robotics and Automation Letters. DOI: 10.1109/LRA.2025.3619687

Journal ref: IEEE Robotics and Automation Letters, vol. 10, no. 11, pp. 12109-12116, Nov. 2025

DOI: 10.1109/LRA.2025.3619687

Code: https://github.com/HMCL-UNIST/Continual-

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Adaptation — 43× in this paper · explained in 1 episode
• Continual Learning — 33× in this paper · explained in 2 episodes
• Catastrophic Forgetting — 8× in this paper · explained in 5 episodes
• Steering — 6× in this paper · explained in 2 episodes
• Generative Model — 4× in this paper · explained in 2 episodes
• International Conference on Robotics and Automation — 4× in this paper
• Ablation — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Activation Function — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Domain Shift — 1× in this paper · explained in 4 episodes
• Epistemic Uncertainty — 1× in this paper · explained in 10 episodes
• Forgetting Measure — 1× in this paper
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generative Models — 1× in this paper · explained in 2 episodes
• Kullback-Leibler (KL) Divergence — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Model Predictive Control (MPC) — 1× in this paper · explained in 5 episodes
• Naive Generative Rehearsal — 1× in this paper
• Negative Log-Likelihood — 1× in this paper
• Point Clouds — 1× in this paper · explained in 2 episodes
• Principal Component Analysis — 1× in this paper
• Principal Component Analysis (PCA) — 1× in this paper · explained in 4 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Self-Supervised Learning — 1× in this paper · explained in 8 episodes
• Stochastic Dynamics — 1× in this paper · explained in 2 episodes
• Technical University of Munich — 1× in this paper

Sources

• DINOv2: Learning Robust Visual Features without Supervision

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