Novel augmented reality interface using a self-powered triboelectric based virtual reality 3D-control sensor.

Triboelectric nanogenerators and sensors have been widely adopted for diversified energy harvesting and sensing applications, but the demonstrations of 3D information sensing and controlling are very limited. In this paper, we present a novel self-powered virtual reality 3D-control sensor (VR-3D-CS) based on triboelectric mechanism for controlling the attitude (both the position and rotation) of object in 3D virtual space. This innovative, cost-effective, simple-designed sensor has a symmetric 3D structure with eight separated sensing electrodes and two touching spheres as the interactive interface with human fingers for 3D force information sensing and VR controlling. Based on the coupling effect of triboelectrification and electrostatic induction, the VR-3D-CS generates different electric output signals in response to different operation manner that can be used to control the attitude of objects in 3D virtual space. The symmetrical 3D configuration design of the sensor enables the detection of 3D force from both the normal direction and shear direction. By employing vector properties of force and signal analysis from the eight sensing electrodes, detection of six-axis directions in 3D space is achieved by triboelectric mechanism for the first time. The VR-3D-CS has been demonstrated to be able to detect normal force in the range of 0–18N. It can resolve the shear force direction with step resolution of at least 15°. Besides, due to the positive output voltage and low internal impedance, the VR-3D-CS is readily compatible with commercial portable signal processing system for signal analysis and controlling. Demonstration of the VR-3D-CS as interactive interface for Augmented Reality (AR) control is successfully realized. Therobust structure, stable outputperformance andself-powered sensing propertyenable the device as an ideal human machine interface towards AR interface, batteryless and energy saving applications.

Researcher / Author: Tao Chen, Mingyue Zhao, Qiongfeng Shi, Zhan Yang, Huicong Liu,

Lining Sun,Jianyong Ouyang, and Chengkuo Lee.

Nano Energy 51 (2018);

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