Papers
13
Total Citations
512
H-Index
10
About
Ameer Tamoor Khan is a robotics and control systems researcher whose work sits at the intersection of bio-inspired computing, cooperative robotics, and intelligent automation. His research focuses primarily on developing advanced control frameworks for robotic manipulators, smart home systems, biped robots, and surgical robotics — areas where he has made consistently impactful contributions over a remarkably productive period. Khan is perhaps best known for pioneering the application of the Beetle Antennae Search (BAS) algorithm to complex robotics challenges, including trajectory optimization for 5-link biped robots (62 citations) and real-time path planning for redundant manipulators. His smart home robotics work has proven especially influential, with his bio-inspired neural network control framework for cooperative robots earning 125 citations and a companion study on human-guided robotic agents attracting a further 97. His model-free approach to soft manipulator trajectory planning using the WJRRT algorithm (63 citations) demonstrates his commitment to practical, computationally efficient solutions. Beyond manipulation and locomotion, Khan has explored autonomous wall-following robots using optimized GRU networks, smart surgical systems under remote-center-of-motion constraints, and even the integration of blockchain technology into distributed robotic control. With over 490 cumulative citations across ten papers, his work continues to shape how researchers approach intelligent, adaptive robotic systems in real-world environments.
Research Focus
Key Achievements
Top Papers
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- 4Trajectory Optimization of 5-Link Biped Robot Using Beetle Antennae Search62 citations · 2021
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- 9Smart surgical control under RCM constraint using bio-inspired network14 citations · 2021
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