Papers
6
Total Citations
86
H-Index
5
About
Kanwal Naveed is a robotics researcher whose work centers on autonomous navigation, simultaneous localization and mapping (SLAM), and adaptive control for mobile robots. His major contributions lie in developing intelligent systems that enable wheeled mobile robots to operate reliably in complex, unstructured environments. Notably, his 2022 paper “Deep introspective SLAM” introduces a deep reinforcement learning approach to predict and avoid tracking failure in visual SLAM, a critical advancement for robust long-term autonomy—this work has already garnered 33 citations. He has also systematically evaluated SLAM sensors using the Analytical Hierarchy Process (16 citations) and pioneered adaptive trajectory tracking controllers that handle uncertain robot parameters (14 and 12 citations). His practical engineering impact is demonstrated through the development of an RPLiDAR-based SLAM system fused with IMU data for autonomous navigation, and an automated guided vehicle designed for warehouse automation in Pakistan’s textile industry. With a research portfolio that bridges theoretical control design and real-world deployment, Naveed’s work is shaping the next generation of dependable, self-navigating robots for applications ranging from agriculture to industrial logistics.
Research Focus
Key Achievements
Top Papers
- 1
- 2Investigation of Widely Used SLAM Sensors Using Analytical Hierarchy Process16 citations · 2022
- 3
- 4Adaptive path tracking control design for a wheeled mobile robot12 citations · 2017
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