Papers

45

Total Citations

668

H-Index

15

About

Bill Goodwine’s research bridges the frontiers of distributed robotics, nonlinear control theory, and fractional-order dynamics, with a focus on systems that are stratified, symmetric, or multi-agent. He is best known for developing the MICAbot platform (105 citations), an inexpensive and flexible robotic system that enabled large-scale distributed robotics and mobile sensor network experiments. His foundational work on controllability and motion planning for stratified configuration spaces—systems with piecewise-differentiable dynamics, such as quasi-static legged robots and finger gaiting—has been widely influential, with key papers earning 51 and 48 citations. Goodwine also pioneered the use of fractional-order differential equations to model multi-robot systems, showing that complex inter-generational dynamics can be captured with reduced-order models (41 citations). His later work on health monitoring via fractional-order system identification (32 citations) and terrain-blind walking control for underactuated bipeds (23 citations) demonstrates a sustained commitment to both theory and application. Across his career, Goodwine has advanced the understanding of how symmetry, stratification, and fractional calculus can simplify and solve challenging problems in robotics and control.

Research Focus

Key Achievements

15
H-Index
45
Papers
668
Total Citations
15
Avg Citations/Paper
🏆 Most Cited Paper
MICAbot: a robotic platform for large-scale distributed robotics
105 citations · 2004
📈 Most Prolific Year: 2004 (5 Papers)
🤝 Key Collaborators: 20
🏛 Institutions: University of Notre Dame, California Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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