Visual Navigation Task

Visual navigation research focuses on enabling agents, such as robots, to navigate environments using visual input, aiming to achieve efficient and robust goal-directed movement. Current research emphasizes developing models that handle diverse goal specifications (e.g., images, language, coordinates), addressing challenges like partial observability, and incorporating prosocial behaviors for safe human-robot interaction. These advancements leverage deep reinforcement learning, often incorporating attention mechanisms and novel reward shaping techniques, and are driving progress in robotics, autonomous driving, and embodied AI.