Are We There Yet? Learning to Localize in Embodied Instruction Following

by   Shane Storks, et al.

Embodied instruction following is a challenging problem requiring an agent to infer a sequence of primitive actions to achieve a goal environment state from complex language and visual inputs. Action Learning From Realistic Environments and Directives (ALFRED) is a recently proposed benchmark for this problem consisting of step-by-step natural language instructions to achieve subgoals which compose to an ultimate high-level goal. Key challenges for this task include localizing target locations and navigating to them through visual inputs, and grounding language instructions to visual appearance of objects. To address these challenges, in this study, we augment the agent's field of view during navigation subgoals with multiple viewing angles, and train the agent to predict its relative spatial relation to the target location at each timestep. We also improve language grounding by introducing a pre-trained object detection module to the model pipeline. Empirical studies show that our approach exceeds the baseline model performance.



page 1

page 4


Towards Navigation by Reasoning over Spatial Configurations

We deal with the navigation problem where the agent follows natural lang...

Scene-Intuitive Agent for Remote Embodied Visual Grounding

Humans learn from life events to form intuitions towards the understandi...

Mapping Instructions to Actions in 3D Environments with Visual Goal Prediction

We propose to decompose instruction execution to goal prediction and act...

Navigating an Infinite Space with Unreliable Movements

We consider a search problem on a 2-dimensional infinite grid with a sin...

Pre-Learning Environment Representations for Data-Efficient Neural Instruction Following

We consider the problem of learning to map from natural language instruc...

Object-and-Action Aware Model for Visual Language Navigation

Vision-and-Language Navigation (VLN) is unique in that it requires turni...

Chasing Ghosts: Instruction Following as Bayesian State Tracking

A visually-grounded navigation instruction can be interpreted as a seque...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.