Papers
6
Total Citations
95
H-Index
6
About
Muddasar Anwar is a robotics researcher whose work spans soft robotics, wearable assistive devices, and industrial automation — bridging the gap between biomimetic design principles and real-world engineering applications. His most recognized contributions include the development of a Supernumerary Robotic Finger (SRF) inspired by the Fin Ray® effect, a wearable device designed to assist patients with sensorimotor hand impairments, which has garnered 25 citations. Closely related, his soft closed-chain modular gripper — also Fin Ray-inspired — has attracted 24 citations, demonstrating his sustained interest in biologically-inspired, underactuated robotic systems for both medical and industrial contexts. Beyond soft robotics, Anwar has made meaningful contributions to precision manufacturing automation. His laser-guided robotic calibration method (17 citations) addresses critical accuracy challenges in aerospace manufacturing, while subsequent work on integrating laser profile sensors with robotic arms and applying data analytics to robotic drilling processes highlights his expertise in sensor fusion and intelligent automation. His exploration of machine learning for aerospace robot-assistance further underscores his interdisciplinary approach. With a growing citation record across assistive technology and smart manufacturing, Anwar represents a versatile voice at the intersection of robotics, biomimetics, and industrial intelligence.
Research Focus
Key Achievements
Top Papers
- 1
- 2Modeling and prototyping of a soft closed-chain modular gripper24 citations · 2019
- 3
- 4
- 5Introducing data analytics to the robotic drilling process11 citations · 2018
- 6