Papers
3
Total Citations
13
H-Index
3
About
Selorm Garfo is an emerging robotics and autonomous systems researcher whose work centers on the design, control, and real-world implementation of Unmanned Ground Vehicles (UGVs). His most significant contributions lie at the intersection of advanced control theory and autonomous navigation, with a particular focus on Model Predictive Control (MPC) as a framework for enabling robots to operate safely in hazardous environments such as nuclear power plants and chemical facilities. His 2022 paper on improved MPC system design for unmanned ground vehicles has garnered 6 citations, establishing him as a contributor to practical autonomous control methodologies. Building on this foundation, Garfo extended his research to incorporate LiDAR-based sensing for real-time obstacle detection and avoidance, demonstrating a systems-level approach to robot navigation that bridges perception and control. His review of nature-inspired robots such as DIGIT and SPOT reflects a broader intellectual curiosity about bio-inspired robotics and the evolving landscape of autonomous systems. With a growing citation record across multiple research threads, Garfo represents a promising voice in the field of intelligent ground robotics, contributing work that has clear implications for search and rescue, industrial automation, and human-robot collaboration.
Research Focus
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