Papers
14
Total Citations
109
H-Index
5
About
Muhammad Bilal Kadri is a robotics and autonomous systems researcher whose work centers on mobile robot localization, multi-sensor fusion, and multi-agent formation control. He is perhaps best known for his contributions to sensor fusion methodologies that integrate GPS, Inertial Navigation Systems (INS), and odometer data to achieve robust and accurate robot localization in both indoor and outdoor environments. His 2020 paper on information fusion of these three sensor modalities has garnered 33 citations, while his foundational 2016 work on Kalman Filter-based sensor fusion has accumulated 26 citations, together establishing him as a notable voice in the localization community. Beyond localization, Kadri has made meaningful contributions to decentralized formation control of non-holonomic and aerial robots, exploring artificial potential fields and asynchronous planning strategies for robot swarms operating in dynamic environments. His more recent work extends into UAV systems, including an open-source ROS2 framework for outdoor UAV dataset generation and multi-rotor customization pipelines, reflecting a forward-looking commitment to reproducible research infrastructure. Spanning nearly two decades, from neural-based navigation in 2008 to aerial swarm planning in 2024, Kadri's career demonstrates sustained and evolving engagement with the core challenges of autonomous mobile robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Sensor fusion of INS, odometer and GPS for robot localization26 citations · 2016
- 3Robot Localization in Indoor and Outdoor Environments by Multi-sensor Fusion10 citations · 2018
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- 5OS-RFODG: Open-source ROS2 framework for outdoor UAV dataset generation5 citations · 2025
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