Arthur Ollanda

Papers

Total Citations

H-Index

About

Arthur Ollanda is a robotics researcher whose work focuses on the development of affordable, open-source autonomous systems, with a particular emphasis on Simultaneous Localization and Mapping (SLAM) for indoor service robots. His most-cited paper, "Application of Simultaneous Localization and Mapping in the Development of an Autonomous Robot" (2022, 9 citations), addresses a critical industrial challenge: the inefficient allocation of human resources to repetitive tasks. By demonstrating how SLAM can enable low-cost robots to navigate and operate autonomously in indoor environments, Ollanda contributes to making service robotics more accessible and practical for small-to-medium enterprises. His research bridges the gap between theoretical SLAM algorithms and real-world deployment, emphasizing open-source solutions to reduce barriers to entry. While his citation count is early-stage, his work signals a growing interest in democratizing robotics for everyday industrial use. Ollanda’s contributions are particularly relevant for students and researchers exploring cost-effective automation, offering a blueprint for building functional autonomous robots without proprietary hardware.