Papers
1
Total Citations
5
H-Index
1
About
Saad Waseem is a robotics researcher whose work centers on warehouse automation, mobile robot navigation, and swarm robotics. His most cited contribution, "Development and Implementation of Enhanced Shortest Path Algorithm for Navigation of Mobile Robot for Warehouse Automation (MRWA)" (2019, 5 citations), introduces a novel shortest path algorithm designed for dynamic environments. A key innovation is the use of a grid of passive RFID tags for precise localization of swarm robots, enabling efficient and scalable coordination without expensive sensors. This work directly addresses the challenge of real-time path planning in cluttered, changing industrial spaces, offering a cost-effective solution for modern logistics. Waseem’s research bridges theoretical algorithm design with practical deployment, demonstrating how low-cost RFID infrastructure can support robust multi-robot systems. His contributions are particularly relevant to the growing field of autonomous warehousing, where reliability and efficiency are paramount. By focusing on accessible technology and clear implementation, Waseem provides a foundation for future advances in swarm navigation and industrial automation.
Research Focus
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Top Papers
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