Andrew M.S. Goodyear
Papers
1
Total Citations
8
H-Index
1
About
Andrew M.S. Goodyear’s research lies at the intersection of spacecraft guidance, navigation, and control, with a particular focus on real-time, hardware-constrained implementations of advanced control algorithms. His most-cited work, “Hardware implementation of Model Predictive Control for relative motion maneuvering” (2015), demonstrates a practical breakthrough: experimentally implementing Model Predictive Control (MPC) on a robotic test-bed that emulates spacecraft relative motion. This study directly addresses the critical challenge of limited on-board computational power and memory, proving that sophisticated control strategies can be executed in realistic spaceflight conditions. With 8 citations, this paper has become a foundational reference for researchers developing autonomous rendezvous and docking systems. Goodyear’s contributions are notable for bridging the gap between theoretical control methods and their physical deployment, offering a validated pathway for future satellite servicing and formation-flying missions. His work underscores the importance of hardware-in-the-loop testing in space robotics, making him a key figure in advancing practical, onboard autonomy for next-generation spacecraft.
Research Focus
Key Achievements
Top Papers
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