Sandra Dang
Papers
1
Total Citations
3
H-Index
1
About
Sandra Dang is a robotics researcher specializing in human-robot interaction (HRI) and sensor fusion, with a focus on intuitive control systems. Her most cited work, "Integrating Human Hand Gestures with Vision Based Feedback Controller to Navigate a Virtual Robotic Arm" (2020), introduces a real-time hybrid control algorithm that combines inertial measurement unit (IMU) data from a Myo Gesture Control Armband with vision-based feedback to operate a 6-DOF Kinova virtual robotic arm. This contribution advances gesture-based teleoperation by enhancing precision and responsiveness in virtual environments. Though early in her career, Dang's work demonstrates a strong interdisciplinary approach, merging embedded systems, computer vision, and robotics. Her research holds potential for applications in assistive technologies and remote manipulation, where natural human gestures can replace traditional controllers. With 3 citations to date, her foundational paper signals growing interest in accessible, multimodal HRI systems. Dang’s achievements reflect a commitment to bridging human intent and robotic action, laying groundwork for future innovations in intuitive human-machine collaboration.
Research Focus
Key Achievements
Top Papers
- 1