Robot Navigation

Autonomous navigation — moving through unstructured environments while avoiding obstacles — spans indoor service robots to outdoor last-mile delivery. Classical SLAM (simultaneous localization and mapping) methods like ORB-SLAM still dominate mapping, but end-to-end learning approaches using habitat simulators (Habitat 2.0, iGibson) show promise for semantic navigation ("go to the kitchen"). The Habitat Challenge results reveal that modular pipelines (map → plan → act) consistently beat monolithic learned policies, suggesting that full end-to-end navigation is still years away from displacing classical stacks in production.