Frontier Based Exploration

Frontier-based exploration in robotics focuses on efficiently mapping unknown environments by systematically targeting and navigating to the boundaries ("frontiers") of explored areas. Current research emphasizes improving exploration efficiency through techniques like integrating deep reinforcement learning (e.g., TD3) with heuristic optimization to select optimal frontiers and plan efficient paths, and employing cooperative multi-robot strategies with heterogeneous sensors and task allocation algorithms. This research is crucial for advancing autonomous navigation in diverse applications, including search and rescue, autonomous driving, and space exploration, by enabling robots to effectively explore and map complex, unstructured environments.