InstructNav: Zero-shot System for Generic Instruction Navigation in Unexplored Environment
Yuxing Long, Wenzhe Cai, Hongcheng Wang, Guanqi Zhan, Hao Dong

TL;DR
InstructNav is a novel zero-shot instruction navigation system that unifies various navigation tasks without prior training, outperforming existing methods and demonstrating robustness in real-world indoor environments.
Contribution
It introduces Dynamic Chain-of-Navigation and Multi-sourced Value Maps to enable generic, zero-shot instruction navigation across diverse tasks without training or maps.
Findings
First zero-shot completion of R2R-CE task.
Outperforms task-trained methods on zero-shot benchmarks.
Demonstrates robustness in real robot experiments.
Abstract
Enabling robots to navigate following diverse language instructions in unexplored environments is an attractive goal for human-robot interaction. However, this goal is challenging because different navigation tasks require different strategies. The scarcity of instruction navigation data hinders training an instruction navigation model with varied strategies. Therefore, previous methods are all constrained to one specific type of navigation instruction. In this work, we propose InstructNav, a generic instruction navigation system. InstructNav makes the first endeavor to handle various instruction navigation tasks without any navigation training or pre-built maps. To reach this goal, we introduce Dynamic Chain-of-Navigation (DCoN) to unify the planning process for different types of navigation instructions. Furthermore, we propose Multi-sourced Value Maps to model key elements in…
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Taxonomy
TopicsMultimodal Machine Learning Applications · Robotics and Automated Systems · Educational Technology and Assessment
