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Pera Swarm Active Localization and Navigation

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Overview

This research aims to develop a navigation and path-planning algorithm that integrates visual SLAM with reinforcement learning for a ground-aerial multi-vehicle system. Autonomous vehicles have become essential for extreme environments such as search and rescue, disaster relief, and infrastructure inspection, where human presence is limited. The combination of unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) enhances mission efficiency by leveraging the complementary strengths of both systems—UGVs provide endurance and payload capacity, while UAVs offer aerial surveillance and rapid maneuverability.