Steban Soto
Papers
2
Total Citations
14
H-Index
2
About
Steban Soto is a robotics researcher specializing in localization for autonomous systems operating in extreme environments. His work focuses on overcoming the limitations of traditional electromagnetic communications in lossy media such as underwater and underground settings. Soto’s major contributions center on the use of magnetic induction (MI) as a robust alternative for robot localization in swarm applications, including foraging and exploration. His 2020 paper, “Underwater Robot Localization Using Magnetic Induction: Noise Modeling and Hardware Validation” (9 citations), provides foundational noise models and experimental validation for MI-based localization in challenging aquatic environments. In a companion study, “Localization using a Particle Filter and Magnetic Induction Transmissions: Theory and Experiments in Air” (5 citations), Soto extended this approach to terrestrial settings, demonstrating the versatility of MI for navigation and collision avoidance. His work bridges theory and practice, offering scalable solutions for swarms operating where GPS and radio signals fail. By advancing particle filter algorithms and hardware-validated models, Soto is shaping the future of resilient, autonomous exploration in subterranean and subsea domains—critical for environmental monitoring, infrastructure inspection, and search-and-rescue missions.
Research Focus
Key Achievements
Top Papers
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- 2