Muhammad Siddique Ahmed Khan

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About

Muhammad Siddique Ahmed Khan is a robotics researcher specializing in autonomous navigation, swarm intelligence, and multi-robot systems. His work focuses on developing algorithms for simultaneous localization and mapping (SLAM) and coordinated search-and-rescue operations. In his most cited paper (6 citations), Khan presents a sonar-based SLAM solution using occupancy grid mapping and dead reckoning for autonomous differential drive robots in indoor environments, demonstrating practical approaches to environmental mapping. He has made significant contributions to swarm robotics, proposing novel multi-robot search algorithms that employ timed random switching between exploration strategies (4 citations) and probabilistic finite state machines combined with Lennard-Jones potential functions (3 citations) to improve decentralized search and rescue efficiency. His research addresses critical challenges in robotic exploration, including map construction from sonar data and coordinated swarm behavior using variable and fixed distance repulsion mechanisms. Khan’s work has implications for autonomous systems in disaster response and indoor navigation, with his algorithms offering scalable solutions for multi-robot coordination. His contributions advance the fields of SLAM and swarm robotics, providing foundational approaches for future autonomous robotic systems.