Ian Taylor
Papers
5
Total Citations
949
H-Index
5
About
Ian Taylor is a robotics researcher whose work sits at the intersection of robotic manipulation, tactile sensing, and computer vision. He is perhaps best known for his influential series of papers on robotic pick-and-place systems capable of grasping and recognizing both known and novel objects in cluttered environments — work that has collectively accumulated over 700 citations across its conference and journal iterations. A defining contribution of this research is its ability to generalize across a wide range of object categories without requiring task-specific training data, a significant step toward practical, deployable robotic systems. Taylor has also made substantial contributions to tactile sensing hardware through his work on GelSlim 3.0, a compact tactile-sensing finger that measures shape, force, and slip in real time, garnering over 210 citations since 2022. His more recent work, SimPLE, addresses the longstanding tension between generality and precision in robotic manipulation by training visuotactile policies in simulation. Across his career, Taylor has consistently pushed the boundaries of how robots perceive and interact with the physical world, making his research essential reading for anyone working in robot learning, grasping, or sensor design.
Research Focus
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Top Papers
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