Papers
13
Total Citations
340
H-Index
10
About
Firas Abi-Farraj is a robotics researcher whose work sits at the intersection of teleoperation, haptic feedback, and shared control — fields with critical applications in nuclear decommissioning, robotic surgery, and complex remote manipulation. His research addresses a fundamental challenge: how humans and autonomous systems can collaborate effectively when operating robots in hazardous or unstructured environments. Abi-Farraj's most influential contribution is his development of haptic shared-control architectures, enabling robotic systems to guide human operators through complex grasping and cutting tasks via intuitive force feedback. His 2019 paper on guided multi-target robotic grasping has accumulated 71 citations, while his visual-based shared control framework (2016, 54 citations) and learning-based shared control approach (2017, 48 citations) have further cemented his reputation in the field. Notably, he has extended these principles to humanoid robot balancing and legged manipulators, demonstrating breadth across robotic platforms. His work is directly motivated by real-world impact — specifically Europe's monumental nuclear waste remediation challenge — and has been validated through rigorous user evaluations. More recently, his integration of Model Predictive Control with haptic teleoperation signals exciting directions for high-dimensional robotic systems. With over 330 cumulative citations, Abi-Farraj's research meaningfully advances safe, intuitive human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1
- 2A visual-based shared control architecture for remote telemanipulation54 citations · 2016
- 3A learning-based shared control architecture for interactive task execution48 citations · 2017
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- 8Collision detection and identification for a legged manipulator16 citations · 2022
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