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Language-Aligned Waypoint (LAW) Supervision for Vision-and-Language Navigation in Continuous Environments

About

In the Vision-and-Language Navigation (VLN) task an embodied agent navigates a 3D environment, following natural language instructions. A challenge in this task is how to handle 'off the path' scenarios where an agent veers from a reference path. Prior work supervises the agent with actions based on the shortest path from the agent's location to the goal, but such goal-oriented supervision is often not in alignment with the instruction. Furthermore, the evaluation metrics employed by prior work do not measure how much of a language instruction the agent is able to follow. In this work, we propose a simple and effective language-aligned supervision scheme, and a new metric that measures the number of sub-instructions the agent has completed during navigation.

Sonia Raychaudhuri, Saim Wani, Shivansh Patel, Unnat Jain, Angel X. Chang• 2021

Related benchmarks

TaskDatasetResultRank
Vision-Language NavigationR2R-CE (val-unseen)
Success Rate (SR)35
266
Vision-Language NavigationRxR-CE (val-unseen)
SR8
172
Vision-and-Language NavigationR2R-CE (val-seen)
SR37
49
Vision-and-Language NavigationVLN-CE 1.0 (val-unseen)
Navigation Error (NE)6.83
20
Vision-and-Language NavigationVLN-CE 1.0 (val-seen)
Navigation Error (NE)6.35
20
Vision-Language NavigationRxR-Habitat English (val seen)
Trajectory Length6.27
3
Vision-Language NavigationRxR-Habitat English Unseen (val)
Trajectory Length (TL)4.01
3
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