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About

Jorge Nieto is a robotics researcher whose work centers on autonomous navigation, path planning, and teleoperation for mobile robots operating in uncertain environments. His most influential contribution, the 2010 paper "Online path planning based on Rapidly-Exploring Random Trees" (28 citations), introduces an innovative online algorithm that leverages Rapidly-Exploring Random Trees (RRT) with two novel heuristics to generate collision-free paths in real time—a critical advance for autonomous robot navigation. Building on this, his 2011 work "Toward safe and stable time-delayed mobile robot teleoperation through sampling-based path planning" (13 citations) tackles the challenge of variable time delays in teleoperation, integrating probabilistic path planning with a prediction module to enhance safety and stability in partially unknown environments. Beyond algorithmic contributions, Nieto developed RACK (Robotics Application Construction Kit), a framework for rapid real-time application development in automation, presented in 2013. His research bridges theoretical planning methods with practical deployment concerns, addressing key bottlenecks in autonomous and remotely operated robotics. With a focused portfolio that has garnered over 47 citations, Nieto’s work continues to influence the design of robust, real-time navigation systems for mobile robots.