Susanne Still

University of Hawaiʻi at Mānoa, Princeton University

Papers

Total Citations

H-Index

About

Susanne Still is a pioneering researcher at the intersection of neuromorphic engineering and robotics, whose work has fundamentally advanced bio-inspired locomotion control. Her key research areas include neuromorphic VLSI circuit design, central pattern generator (CPG) modeling, and adaptive gait control for legged robots. Still’s most significant contribution is the development of a neuromorphic walking gait controller that mimics the spinal CPGs found in vertebrate nervous systems, implemented directly on a custom VLSI chip. This hardware-based approach, detailed in her highly cited 2006 paper (44 citations), enables real-time, energy-efficient coordination of leg phasing in four-legged robots without the need for heavy computational resources. Her earlier work (2000, 17 citations) further demonstrated the integration of this neuromorphic chip with support vector learning algorithms, creating a hybrid system that adapts gaits to terrain changes. While her total citation count is modest, Still’s impact lies in her foundational proof-of-concept: she showed that biological neural principles could be directly translated into silicon to achieve robust, autonomous locomotion. Her research remains a cornerstone for engineers seeking to build efficient, animal-like walking robots.