ROS-X-Habitat: Bridging the ROS Ecosystem with Embodied AI
This work addresses the problem of interoperability between embodied AI and robotics ecosystems for researchers and developers, but it is incremental as it builds on existing platforms.
The authors tackled the challenge of integrating the AI Habitat platform for embodied learning agents with other robotics resources via ROS, resulting in a software interface that enables cross-platform compatibility with minimal impact on navigation performance and simulation speed.
We introduce ROS-X-Habitat, a software interface that bridges the AI Habitat platform for embodied learning-based agents with other robotics resources via ROS. This interface not only offers standardized communication protocols between embodied agents and simulators, but also enables physically and photorealistic simulation that benefits the training and/or testing of vision-based embodied agents. With this interface, roboticists can evaluate their own Habitat RL agents in another ROS-based simulator or use Habitat Sim v2 as the test bed for their own robotic algorithms. Through in silico experiments, we demonstrate that ROS-X-Habitat has minimal impact on the navigation performance and simulation speed of a Habitat RGBD agent; that a standard set of ROS mapping, planning and navigation tools can run in Habitat Sim v2; and that a Habitat agent can run in the standard ROS simulator Gazebo.