Arlene John
Papers
2
Total Citations
5
H-Index
2
About
Arlene John’s research lies at the intersection of robotics, control systems, and biomedical signal processing, with a focus on enhancing autonomous navigation and human-robot interaction. Her work on skid-steered robots addresses the fundamental challenge of modeling and controlling these robust outdoor platforms, which are prone to complex sliding and rolling dynamics during curvilinear motion. By improving motion and pose estimation, her 2017 paper provides a foundation for more reliable surveillance and mapping applications, earning 3 citations. In parallel, John has pioneered the use of biological signals for robotic control. Her 2015 study introduces a novel method leveraging electromyography (EMG) signals, combined with entropy and zero-crossing rate analysis, to intuitively command a robotic arm. This work, with 2 citations, highlights her ability to bridge engineering and healthcare, offering accessible control solutions for medical and industrial robotics. Though early in her career, John’s contributions demonstrate a clear trajectory toward integrating robust mechanical design with intelligent, human-centric control systems—a promising direction for future autonomous and assistive technologies.
Research Focus
Key Achievements
Top Papers
- 1
- 2