Abdul Qadir Khan
Papers
1
Total Citations
8
H-Index
1
About
Abdul Qadir Khan is a robotics researcher whose work focuses on safe and intelligent navigation in dynamic, human-populated environments. His primary research areas include motion planning, collision avoidance, and human-robot interaction, with a particular emphasis on developing algorithms that account for the inherent unpredictability of pedestrian behavior. His most cited work, "Collision Avoidance from Multiple Passive Agents with Partially Predictable Behavior" (2017), addresses the critical challenge of enabling robots to navigate crowded spaces while respecting their own kinodynamic constraints. By proposing a novel navigational strategy that models the partially predictable movements of other agents, Khan’s research bridges the gap between theoretical motion planning and real-world deployment. This contribution is foundational for applications in autonomous delivery robots, service robotics, and assistive technologies. With 8 citations, this paper has laid groundwork for subsequent studies in socially-aware navigation. Khan’s work is particularly notable for its practical approach to a complex problem, offering solutions that enhance robot autonomy and safety in unpredictable settings. His research continues to inspire advancements in how robots coexist and interact with humans in shared spaces.
Research Focus
Key Achievements
Top Papers
- 1