Andrew G. Gillies

University of California, Berkeley

Papers

6

Total Citations

323

H-Index

6

About

Andrew G. Gillies is a leading researcher in bio-inspired robotics and materials, specializing in gecko-inspired adhesives and vertical climbing robots. His work bridges fundamental materials science and practical robot locomotion, with over 320 citations across his most influential papers. Gillies made a landmark contribution with "Controllable Particle Adhesion with a Magnetically Actuated Synthetic Gecko Adhesive" (105 citations), demonstrating how magnetic actuation can achieve repeatable, high-performance particle capture and release—a breakthrough for reusable adhesives, micro-manipulation, and solar panel cleaning. He also pioneered the CLASH robot (60 citations), a 10 cm, 15 g hexapedal climber that uses a single actuator and passive spine foot mechanisms to ascend vertical loose cloth at 15 cm/s, solving a key challenge in soft-surface locomotion. His work on shear adhesion ("Shear Adhesion Strength of Thermoplastic Gecko-Inspired Synthetic Adhesive Exceeds Material Limits," 58 citations) showed that stiff polymer adhesives can exceed material strength limits, enabling high-cycle applications like robot feet. Additionally, Gillies advanced dry self-cleaning properties of fibrillar structures (47 citations) and dynamic climbing of smooth surfaces (46 citations), where he integrated gecko adhesives with elastomer tendons and remote-center-of-motion ankles for rapid engagement. His research is foundational for next-generation climbing robots, reusable adhesives, and automated surface-cleaning systems.

Research Focus

Key Achievements

6
H-Index
6
Papers
323
Total Citations
54
Avg Citations/Paper
🏆 Most Cited Paper
Controllable Particle Adhesion with a Magnetically Actuated Synthetic Gecko Adhesive
105 citations · 2013
📈 Most Prolific Year: 2011 (3 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: University of California, Berkeley

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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