Facebook AI Research (FAIR) is dedicated to advancing the field of socially intelligent robotics. The main goal is to develop robots that can assist with everyday tasks while adapting to the unique preferences of their human partners. The work involves digging deeper into embedded systems to lay the foundation for the next generation of AR and VR experiences. The goal is to make robotics an integral part of our lives, reducing the burden of routine tasks and improving the quality of life of individuals. FAIR’s multifaceted approach highlights the importance of merging AI, AR, VR and robotics to create a future where technology seamlessly augments our daily experiences and empowers us to act in unimaginable ways previously.
FAIR has made three significant advances to address scalability and security challenges when training and testing AI agents in physical environments:
- Habitat 3.0 is a high-quality simulator for robots and avatars, facilitating human-robot collaboration in a home-like environment.
- The Habitat Synthetic Scenes Dataset (HSSD-200) is a 3D dataset designed by artists to provide exceptional generalization when training navigation agents.
- The HomeRobot platform provides an affordable home robot assistant for open-vocabulary tasks in simulated and physical environments, accelerating the development of AI agents capable of assisting humans.
Habitat 3.0 is a simulator designed to facilitate robotics research by allowing algorithms to be quickly and safely tested in virtual environments before deploying them on physical robots. It enables collaboration between humans and robots when performing everyday tasks and includes realistic humanoid avatars to enable AI training in various home environments. Habitat 3.0 provides benchmark tasks that promote robot-human collaborative behaviors in real-world indoor scenarios, such as cleaning and navigation, introducing new avenues for exploring socially embodied AI.
HSSD-200 is a synthetic 3D scene dataset that provides a more realistic and compact option for training robots in simulated environments. It includes 211 high-quality 3D sets reproducing physical interiors and contains 18,656 models from 466 semantic categories. Although smaller in scale, ObjectGoal navigation agents trained on HSSD-200 perform comparably to those introduced on much larger datasets. In some cases, training on just 122 HSSD-200 scenes outperforms agents trained on 10,000 scenes from prior datasets, demonstrating its effectiveness in generalizing to physical world scenarios.
In the field of robotics research, having a shared platform is crucial. HomeRobot seeks to address this need by setting motivating tasks, providing versatile software interfaces, and fostering community engagement. Open-vocabulary mobile manipulation provides a motivating task, challenging robots to manipulate objects in diverse environments. The HomeRobot library supports navigation and manipulation for Hello Robot’s Stretch and Boston Dynamics’ Spot, both in simulated and physical environments, supporting replication of experiments. The platform emphasizes transferability, modularity and basic agents, with a benchmark showing a 20% pass rate on physical world tests.
The field of embodied AI research is constantly evolving to respond to dynamic environments that involve human-robot interactions. Facebook AI’s vision for developing socially intelligent bots is not limited to static scenarios. Instead, they focus on collaboration, communication, and predicting future states in dynamic contexts. To achieve this, researchers use Habitat 3.0 and HSSD-200 as tools to train AI models in simulation. Their goal is to attend and adapt to human preferences while deploying these trained models in the physical world to evaluate their real-world performance and capabilities.
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Sana Hassan, Consulting Intern at Marktechpost and a dual degree student at IIT Madras, is passionate about applying technology and AI to address real-world challenges. With a keen interest in solving practical problems, he brings a fresh perspective to the intersection of AI and real-world solutions.
