Time-to-Collision Based Dynamic Obstacle Avoidance Using Pretrained Vision Models for Robots in Unstructured Environments

The paper proposes a data-efficient method that uses pretrained vision models to help mobile robots avoid dynamic obstacles in unstructured real-world environments.

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