CHALET: Cornell House Agent Learning Environment
This provides a new benchmark environment for AI research in robotics and embodied AI, though it is incremental as it builds on existing simulation tools.
The authors introduced CHALET, a 3D house simulator with 58 rooms and 10 configurations, designed to train and evaluate autonomous agents on household activities like object manipulation and appliance toggling.
We present CHALET, a 3D house simulator with support for navigation and manipulation. CHALET includes 58 rooms and 10 house configuration, and allows to easily create new house and room layouts. CHALET supports a range of common household activities, including moving objects, toggling appliances, and placing objects inside closeable containers. The environment and actions available are designed to create a challenging domain to train and evaluate autonomous agents, including for tasks that combine language, vision, and planning in a dynamic environment.