The paper shows that monocular depth estimation from foundation models, enhanced with SLAM rescaling, edge masking, and temporal smoothing, can match LiDAR for off-road robot navigation.
The marathon 2: A navigation system
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An agentic LLM/LVM framework generates adaptive behavior trees on-the-fly for AV navigation in CARLA+Nav2 simulation, succeeding in obstacle avoidance where static BTs fail.
citing papers explorer
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An Open-Source LiDAR and Monocular Off-Road Autonomous Navigation Stack
The paper shows that monocular depth estimation from foundation models, enhanced with SLAM rescaling, edge masking, and temporal smoothing, can match LiDAR for off-road robot navigation.
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From Prompts to Pavement: LMMs-based Agentic Behavior-Tree Generation Framework for Autonomous Vehicles
An agentic LLM/LVM framework generates adaptive behavior trees on-the-fly for AV navigation in CARLA+Nav2 simulation, succeeding in obstacle avoidance where static BTs fail.