3D household task-based dataset created using customised AI2-THOR.
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Updated
Apr 14, 2022 - C#
3D household task-based dataset created using customised AI2-THOR.
Evaluation tasks for ObjectNav models
🚀 Run AI2-THOR with Google Colab
Implementation of "Safe Deep Learning-Based Global Path Planning Using a Fast Collision-Free Path Generator". We present a global path planning method in this project which is based on an LSTM model that predicts safe paths for the desired start and goal points in an environment with polygonal obstacles, using a new loss function (MSE-NER).
Implementation of "Safe Deep Learning-Based Global Path Planning Using a Fast Collision-Free Path Generator". We present a global path planning method in this project which is based on an LSTM model that predicts safe paths for the desired start and goal points in an environment with polygonal obstacles, using a new loss function (MSE-NER).
🏘️ Scaling Embodied AI by Procedurally Generating Interactive 3D Houses
Visual Reaction: Learning to Play Catch with Your Drone
📱👉🏠 Perform conditional procedural generation to generate houses like your own!
🔀 Visual Room Rearrangement
Robothor Environment for RL training, abide `gym` API
CVPR 2024: Language Guided Generation of 3D Embodied AI Environments.
Code for the ICRA 2024 Cook2LTL paper on translating free-form cooking recipes to Linear Temporal Logic (LTL) formulae for robot task planning.
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