Aditya Arun

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About

Aditya Arun is a robotics researcher specializing in indoor simultaneous localization and mapping (SLAM), with a particular focus on leveraging wireless sensing technologies to enhance autonomous navigation systems. His work addresses one of the core challenges in indoor robotics: building robust, resource-efficient localization algorithms that can operate reliably without solely depending on traditional camera and LiDAR setups. Arun's most recognized contribution, "P2SLAM: Bearing Based WiFi SLAM for Indoor Robots" (2022), has garnered 40 citations and represents a significant step forward in multi-sensor fusion for indoor environments. By incorporating WiFi-based bearing measurements as an exteroceptive sensing modality, his approach helps correct the drift inherent in odometry-only systems — a persistent limitation in real-world indoor deployments. Building on this foundation, his 2024 follow-up work, "WAIS: Leveraging WiFi for Resource-Efficient SLAM," extends these ideas toward more computationally economical solutions, addressing the practical constraints of deploying autonomous robots at scale. Arun's research sits at a compelling intersection of wireless communications and robotics, offering pathways to smarter, leaner indoor navigation systems. His growing body of work positions him as an emerging voice in the WiFi-aided SLAM community.