Khaled A. A. Mustafa
Papers
2
Total Citations
35
H-Index
2
About
Khaled A. A. Mustafa is a researcher specializing in autonomous mobile robotics, with a particular focus on deep reinforcement learning (DRL) and simultaneous localization and mapping (SLAM) for intelligent navigation systems. His work addresses one of robotics' most compelling challenges: enabling mobile robots to navigate unknown environments without pre-existing maps, relying solely on onboard sensor data such as raw laser readings and odometry information. Mustafa's most notable contributions center on developing mapless path planning algorithms that harness DRL to produce adaptive, continuous motion control for robots operating in dynamic and unpredictable spaces. His 2019 work introduced a continuous control framework for autonomous navigation, while his 2020 follow-up advanced the field by integrating reward shaping informed by online SLAM knowledge — a creative fusion that improved learning efficiency and navigation performance. Together, these papers have accumulated over 35 citations, reflecting meaningful recognition within the robotics and AI communities. His research is particularly valuable for students and practitioners exploring how intelligent agents can learn robust navigation policies without exhaustive environmental pre-mapping, bridging theoretical reinforcement learning with real-world robotic deployment challenges.
Research Focus
Key Achievements
Top Papers
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