Papers
56
Total Citations
976
H-Index
18
About
A. Pedro Aguiar is a prominent researcher whose work spans autonomous robotics, nonlinear control theory, and multi-vehicle coordination systems. He has made foundational contributions to the motion planning, localization, and control of robotic vehicles operating in challenging environments, with particular emphasis on autonomous underwater vehicles (AUVs) and marine robotics. His 2015 work on range-based AUV localization in unknown ocean currents (110 citations) demonstrated both theoretical rigor and experimental validation, establishing him as a key figure in underwater navigation. Aguiar has also advanced multi-robot coordination, developing energy-optimal motion planning algorithms for vehicle formations (79 citations) and event-based cooperative path following strategies that reduce communication overhead without sacrificing performance. His earlier contributions to nonholonomic robot stabilization and hybrid control systems reflect a career-long engagement with fundamental control challenges, while his 2006 work on minimum-energy state estimation for perspective output systems (68 citations) demonstrates versatility across estimation theory. More recently, his integration of economic optimization within model predictive control frameworks highlights a growing interest in practically deployable autonomous systems. Collectively, his body of work, accumulating hundreds of citations, reflects deep and sustained influence across control engineering, robotics, and autonomous systems research.
Research Focus
Key Achievements
Top Papers
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- 3Minimum-Energy State Estimation for Systems With Perspective Outputs68 citations · 2006
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- 10Automatic bottom-following for underwater robotic vehicles31 citations · 2014