Papers
32
Total Citations
652
H-Index
13
About
Said Ghani Khan is a prominent robotics and control systems researcher whose work spans reinforcement learning, compliance control, and human-robot interaction (HRI). He has made significant contributions to the field of adaptive control, particularly in the context of humanoid robotic arms, where his early work on safe adaptive compliance control and anti-windup compensation helped establish foundational techniques for safer physical interaction between robots and humans. His 2012 overview of reinforcement learning and optimal adaptive control has become a widely referenced resource, accumulating over 230 citations and cementing his reputation as an authority bridging learning-based and classical control paradigms. Khan's research consistently prioritizes human safety, evidenced by his extensive survey on compliance control techniques and his development of integral sliding mode controllers for robotic systems. His work has expanded into rehabilitation robotics, with notable contributions to robotic walk assist devices using reinforcement learning and sliding mode control — addressing real-world accessibility challenges in low-income settings. More recently, he has ventured into precision agriculture, applying deep learning to autonomous robotic spraying systems. With a portfolio spanning foundational theory to applied innovation, Khan's research has collectively attracted hundreds of citations, reflecting his enduring influence across robotics, adaptive control, and intelligent systems communities.
Research Focus
Key Achievements
Top Papers
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- 3Compliance Control and Human–Robot Interaction: Part 1 — Survey45 citations · 2014
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- 8A Novel Adaptive Control Algorithm in Application to a Humanoid Robot Arm19 citations · 2012
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