Chang Lian-jun
Papers
1
Total Citations
4
H-Index
1
About
Chang Lian-jun is a pioneering researcher at the forefront of collaborative robotics, with a specialized focus on integrating deep learning into robotic control and safety systems. His most notable contribution, detailed in his 2025 paper "Research on Zero-Force control and collision detection of deep learning methods in collaborative robots," addresses a critical challenge in human-robot interaction: enabling robots to operate safely alongside humans without force sensors. By leveraging deep learning algorithms, Lian-jun developed a method that allows robots to detect collisions and adjust their movements in real-time, effectively achieving zero-force control. This work, which has already garnered 4 citations shortly after publication, promises to reduce the cost and complexity of collaborative robots, making them more accessible for small and medium-sized enterprises. His research sits at the intersection of artificial intelligence, mechatronics, and safety engineering, offering a scalable solution for next-generation manufacturing and service robotics. Lian-jun’s innovative approach not only advances the field of human-robot collaboration but also sets a new standard for intuitive and safe robotic systems.
Research Focus
Key Achievements
Top Papers
- 1