Arif Khan
Papers
1
Total Citations
11
H-Index
1
About
Arif Khan is a researcher in assistive robotics and human-machine interaction, with a focus on developing intelligent systems that enhance mobility and autonomy for individuals with disabilities. His most-cited work, "A Cognitively Enhanced Collaborative Control Architecture for an Intelligent Wheelchair: Formalization, Implementation and Evaluation" (2018, 11 citations), introduces a novel framework that integrates cognitive modeling with collaborative control, allowing wheelchairs to interpret user intent and adapt to dynamic environments. This architecture bridges the gap between fully autonomous and manual control, prioritizing user safety and comfort while maintaining a sense of agency. Khan’s contributions lie in formalizing shared control strategies that leverage real-time sensor data and user input, advancing the field of human-robot collaboration. Though his citation count reflects a growing niche, his work has been recognized for its practical implications in rehabilitation engineering, offering a scalable model for future assistive technologies. By emphasizing cognitive augmentation over full automation, Khan’s research underscores the importance of user-centered design in robotics, paving the way for more intuitive and responsive mobility aids.
Research Focus
Key Achievements
Top Papers
- 1