Ting Wan

Papers

Total Citations

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About

Ting Wan’s research bridges robotics and human-computer interaction, with a focus on intuitive control systems and adaptive locomotion. Their pioneering work on hand gesture recognition using depth data from Kinect sensors established a foundation for non-contact robot control, achieving 24 citations for demonstrating how sequence-based depth imaging can reliably interpret predefined gestures to command mobile robots. This contribution remains influential in the development of natural user interfaces for autonomous systems. Complementing this, Wan’s design of a hexapod robot introduced a modular, wheel-leg hybrid architecture capable of autonomously navigating varied terrain, using interrupt-based position detection and PWM control to enhance obstacle-surmounting capabilities. Though less cited (7 citations), this work showcases innovative mechanical design for field robotics. Together, these studies reflect Wan’s dual expertise in perception and locomotion, advancing both the cognitive and physical capabilities of robots. Their research continues to inspire applications in assistive technology and search-and-rescue operations, where intuitive control and terrain adaptability are critical.