Finding and Navigating to Humans in Complex Environments for Assistive Tasks

Finding and reaching humans in unseen environments is a major challenge for intelligent agents and social robots. Effective exploration and navigation strategies are necessary to locate the human performing various activities. In this paper, we propose a problem formulation in which the robot is required to locate and reach humans in unseen environments. To tackle this task, we design an approach that makes use of state-of-the-art components to allow the agent to explore the environment, identify the human’s location on the map, and approach them while maintaining a safe distance. To include human models, we utilized Blender to modify the scenes of the Gibson dataset. We conducted experiments using the Habitat simulator, where the proposed approach achieves promising results. The success of our approach is measured by the distance and orientation difference between the robot and the human at the end of the episode. We will release the source code and 3D human models for researchers to benchmark their assistive systems.