Janindu Arukgoda

University of Technology Sydney, Virginia Tech

Papers

Total Citations

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About

Janindu Arukgoda is a robotics researcher whose work focuses on environment representation and high-precision autonomous navigation. His key contributions lie in developing novel map representations for mobile robot localisation, particularly through the introduction of the vector distance function (VDF). This approach offers a continuous derivative at object boundaries—an improvement over traditional unsigned distance transforms—enabling more accurate and stable localisation algorithms. His most cited paper, "Vector Distance Function Based Map Representation for Robot Localisation" (2017, 5 citations), demonstrates this innovation. Arukgoda also advanced autonomous systems with his work on a "Multistage Bayesian Autonomy for High‐Precision Operation in a Large Field" (2018, 3 citations), which provides a generalized framework for robots to perform precise tasks on static targets across expansive environments. His review on environment representation for mobile robot localisation (2017, 3 citations) further consolidates his expertise, surveying distance function techniques that capture spatial geometry. With a focused portfolio addressing core challenges in robot perception and autonomy, Arukgoda’s research offers practical pathways for enhancing the reliability and precision of mobile robots in real-world applications.