Dijun Liu

China Telecom (China), Beijing Enterprises (China)

Papers

Total Citations

171

H-Index

About

Dijun Liu is a leading researcher in robotics and computer vision, with a primary focus on autonomous systems, deep learning for environmental interaction, and simultaneous localization and mapping (SLAM). His most impactful contribution is the development of a deep learning-based robot for autonomously picking up garbage on grass, a pioneering work that has garnered 161 citations. This system integrates a deep neural network for accurate garbage detection with a novel ground segmentation and navigation strategy, enabling fully autonomous operation in unstructured outdoor environments—a significant step toward practical, eco-friendly robotics. Liu has also advanced the field of visual-inertial SLAM, proposing a novel feedback mechanism that improves the balance between real-time performance and localization accuracy, a persistent challenge in robotics. While his SLAM work has received 10 citations, it demonstrates his commitment to refining core navigation technologies. Through these contributions, Liu has established himself as an innovator at the intersection of deep learning and autonomous robotics, addressing real-world problems from environmental cleanup to robust robot perception.