A. Lastra

Papers

Total Citations

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About

A. Lastra’s research centers on human-robot interaction and computer vision, with a particular focus on enabling robots to perceive and respond to human cues in real-world environments. Their most notable contribution is the development of robust, color-based skin detection algorithms, which are critical for robots to identify and track human operators during collaborative tasks. In their 2007 work, “Robust Color-Based Skin Detection for an Interactive Robot,” Lastra introduced a method that effectively handles varying lighting conditions and skin tones, achieving reliable performance in dynamic settings. This foundational approach has influenced subsequent research in interactive robotics, with the paper accumulating over 4 citations—a modest but meaningful impact that underscores its practical relevance. Lastra’s work bridges the gap between low-level visual processing and high-level robotic behavior, demonstrating how robust perception can enhance natural human-robot collaboration. Their contributions are particularly valuable for applications in assistive robotics, manufacturing, and social robotics, where accurate skin detection is a prerequisite for safe and intuitive interaction. By addressing the challenges of real-world variability, Lastra has helped lay the groundwork for more responsive and adaptable robotic systems.