Michael Hoy

UNSW Sydney

Papers

14

Total Citations

664

H-Index

7

About

Michael Hoy is a robotics researcher whose work sits at the intersection of autonomous navigation, motion planning, and collision avoidance for mobile robotic systems. He has made significant contributions to the field through both theoretical analysis and practical algorithm development, addressing some of the most challenging problems in robot autonomy. Hoy is perhaps best known for his landmark 2014 survey, "Algorithms for Collision-Free Navigation of Mobile Robots in Complex Cluttered Environments," which has accumulated an impressive 466 citations and stands as an essential reference for researchers entering the field. This comprehensive review systematically examines techniques that rigorously guarantee collision avoidance for unmanned vehicles operating in unknown environments — a critical safety concern for real-world deployment. Beyond surveying the field, Hoy has advanced original methods for wheeled robot navigation, including shortest-path planning under curvature constraints, boundary-following strategies using sampled range data, and cooperative multi-robot navigation in unknown spaces. His work extends to aerial vehicles, having proposed sliding mode and model predictive control approaches for autonomous helicopter navigation in urban environments. More recently, he has explored reactive navigation among dynamic and deforming obstacles and biologically inspired avoidance strategies, reflecting a broad and evolving research vision. With a body of work spanning theoretical guarantees and practical algorithm design, Hoy has meaningfully shaped how autonomous robots navigate safely through complex real-world environments.

Research Focus

Key Achievements

7
H-Index
14
Papers
664
Total Citations
47
Avg Citations/Paper
🏆 Most Cited Paper
Algorithms for collision-free navigation of mobile robots in complex cluttered environments: a survey
466 citations · 2014
📈 Most Prolific Year: 2011 (4 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: UNSW Sydney

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago