Vladimir Macias

Papers

Total Citations

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About

Vladimir Macias is a researcher in robotics and control theory, with a focus on differential games and optimal navigation. His work centers on the value of information in pursuit-evasion scenarios, where he explores how feedback from sensors and landmarks can optimize decision-making in real-time. In his most-cited paper, "Image feedback based optimal control and the value of information in a differential game" (2018, 28 citations), Macias introduces a framework that uses visual feedback to enhance control strategies, demonstrating how information quality directly impacts performance in adversarial settings. His earlier work, "On the value of information in a differential pursuit-evasion game" (2015, 8 citations), tackles the classic problem of capturing an omnidirectional evader with a Differential Drive Robot (DDR), formalizing the trade-offs between pursuit speed and evader evasion. More recently, in "Single landmark feedback-based time optimal navigation for a differential drive robot" (2021, 4 citations), he extends these ideas to efficient navigation using minimal sensory input. Macias’s contributions bridge theoretical game theory and practical robotics, offering insights into how robots can leverage limited information to achieve optimal outcomes. His research is particularly valuable for students and engineers working on autonomous systems, multi-agent coordination, and sensor-based control.