Papers

2

Total Citations

5

H-Index

2

About

Jalaluddin Khan is a robotics researcher focused on intelligent automation and human-robot interaction. His work centers on developing adaptive robotic systems for complex, real-world environments, with key contributions in fuzzy logic-based vision computing and trainable manipulator design. His 2018 paper, "Complex Environment Fuzzy Vision Computing," introduced a novel approach to path-following robots using fuzzy logic for enhanced navigation in domestic and industrial settings, earning 3 citations for its practical framework. In 2019, Khan advanced the field with "Prototype of Smart Trainable Robotic Arm," a manipulator designed for hazardous environments—such as those involving harmful chemicals or extreme temperatures—where human presence is unsafe. This work, cited 2 times, demonstrated a trainable system capable of pick-and-drop tasks, emphasizing adaptability and safety. While his citation counts reflect an emerging career, Khan’s research bridges foundational robotics concepts with applied solutions, addressing critical needs in automation and hazardous material handling. His achievements highlight a commitment to making robotics more accessible and robust, positioning him as a promising contributor to intelligent systems engineering.

Research Focus

Key Achievements

2
H-Index
2
Papers
5
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Complex Environment Fuzzy Vision Computing
3 citations · 2018
📈 Most Prolific Year: 2018 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: University of Electronic Science and Technology of China

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago