Habitat-Lab is a modular high-level library for end-to-end development in embodied AI. It is designed to train agents to perform a wide variety of embodied AI tasks in indoor environments, as well as develop agents that can interact with humans in performing these tasks. Allowing users to train agents in a wide variety of single and multi-agent tasks (e.g. navigation, rearrangement, instruction following, question answering, human following), as well as define novel tasks. Configuring and instantiating a diverse set of embodied agents, including commercial robots and humanoids, specifying their sensors and capabilities. Providing algorithms for single and multi-agent training (via imitation or reinforcement learning, or no learning at all as in SensePlanAct pipelines), as well as tools to benchmark their performance on the defined tasks using standard metrics.

Features

  • Flexible task definitions
  • Documentation available
  • Diverse embodied agents
  • Training and evaluating agents
  • Human in the loop interaction
  • Examples included

Project Samples

Project Activity

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Categories

Agentic AI

License

MIT License

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Habitat-Lab Web Site

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Additional Project Details

Programming Language

Python

Related Categories

Python Agentic AI Framework

Registered

23 hours ago