Brian Sotolongo

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About

Brian Sotolongo is a researcher in robotics and algorithmic motion planning, with a focus on energy-efficient navigation for autonomous systems. His most-cited work, "Shortest Path Planning with an Energy-Constrained Robot" (2021), addresses a critical challenge in mobile robotics: how to compute optimal paths for robots with limited battery capacity. By modeling a robot that can travel at most a distance B on a full charge, Sotolongo develops algorithms that minimize travel distance while respecting energy constraints, bridging the gap between theoretical path planning and real-world deployment constraints. This contribution is foundational for applications in field robotics, drone delivery, and planetary exploration, where energy is a scarce resource. Though his citation count is modest—2 citations for this paper—his work has been recognized for its practical relevance, and he continues to explore extensions involving recharging stations and dynamic energy consumption models. Sotolongo’s research is particularly valuable for students and engineers designing autonomous systems that must operate reliably in energy-limited environments, offering a rigorous framework for balancing efficiency and endurance.