Research on Intelligent Navigation and Dynamic Obstacle Avoidance of Robots Based on Visual Perception: A Review

In modern robotic autonomous operations, navigation and dynamic interaction in unstructured scenarios are key to achieving efficient operations. However, current research on visual perception-based robotic systems lacks adaptability to unstructuredscenarios and integration with engineering applications. This article reviews visual perception-driven intelligent navigation and dynamic interaction for robotics, analyzing the technical modules of visual SLAM and navigation collaboration, visual object recognition optimization, and multi-node autonomous interaction. The research found that the collaboration between visual SLAM and navigation has mostly been demonstrated in ideal environments, visual recognition algorithms are less adaptable to complex interference, and the engineering integration of "navigation-recognition-interaction" needs to be strengthened. This review aims to establish a solid theoretical foundation for designing robotic systems in low- and medium-complexity scenarios, advance visual perception technology from laboratory research to industrial application, and contribute to breakthroughs and developments in related fields.