Outdoor Robot

Outdoor robot navigation research focuses on enabling robots to autonomously traverse complex, unstructured environments. Current efforts concentrate on improving perception (e.g., using LiDAR, cameras, and GPS data fused with satellite imagery) and robust control algorithms (including fuzzy logic, reinforcement learning, and generative models like Conditional Variational Autoencoders) to handle obstacles, varying terrain, and dynamic conditions. These advancements are crucial for expanding the capabilities of robots in agriculture, delivery services, and other outdoor applications, ultimately leading to more efficient and reliable autonomous systems.