Max Robotics — Global Service Robot Directory + US Certification

About

Harold Murcia’s research bridges the gap between unmanned aerial and ground vehicles, sensor-based perception, and robotic control systems. His most cited work, “Formation Control of UGVs using an UAV as Remote Vision Sensor” (18 citations), demonstrates a pioneering approach to multi-agent coordination, where an aerial drone acts as a remote eye to guide ground robots—a concept vital for search-and-rescue and precision agriculture. In “3D Scene Reconstruction Based on a 2D Moving LiDAR” (14 citations), Murcia advanced low-cost spatial mapping, enabling detailed environmental modeling without expensive 3D sensors. His comparative study on PID versus LQR control for a two-wheeled inverted pendulum robot (11 citations) stands out for its rigorous gray-box modeling using Lagrange dynamics, offering practical insights into balancing and stabilization for mobile robotics. Beyond these contributions, Murcia has developed tools for line-following competition robots and a simulation platform for 3D plant modeling from 2D LiDAR data (3 citations), which leverages geometric information for phenotyping—a step toward automated agricultural analysis. With a portfolio spanning control theory, sensor fusion, and field robotics, Murcia’s work provides foundational techniques for autonomous systems operating in unstructured environments.