Actionet: An Interactive End-To-End Platform For Task-Based Data Collection And Augmentation In 3D Environment

TL;DR

ActioNet is an innovative interactive platform that enables large-scale collection and augmentation of task-based datasets in 3D environments, significantly advancing research in hierarchical task planning for artificial agents.

Contribution

It introduces the first end-to-end platform for task-based dataset generation in 3D environments, creating the largest comprehensive dataset of its kind.

Findings

Collected over 3000 hierarchical task structures and videos.

Augmented videos across 50 scenes to produce over 150,000 videos.

Facilitates research in hierarchical task planning.

Abstract

The problem of task planning for artificial agents remains largely unsolved. While there has been increasing interest in data-driven approaches for the study of task planning for artificial agents, a significant remaining bottleneck is the dearth of large-scale comprehensive task-based datasets. In this paper, we present ActioNet, an interactive end-to-end platform for data collection and augmentation of task-based dataset in 3D environment. Using ActioNet, we collected a large-scale comprehensive task-based dataset, comprising over 3000 hierarchical task structures and videos. Using the hierarchical task structures, the videos are further augmented across 50 different scenes to give over 150,000 video. To our knowledge, ActioNet is the first interactive end-to-end platform for such task-based dataset generation and the accompanying dataset is the largest task-based dataset of such comprehensive nature. The ActioNet platform and dataset will be made available to facilitate research in hierarchical task planning.