Xuan Zhao,Zhuo Kang,Qingliang Liao,Zheng Zhang,Mingyuan Ma,Qian Zhang,Yue Zhang
In the Internet of things (IoT), motion sensor in the perceptual layer is at the forefront of the information collection, which plays a crucial role in the IoT. However, with a large number of commercial applications, several problems of motion sensor limit the development of IOT such as poor portability, poor environmental adaptability, and high energy consumption, etc. In this work, an ultralight, self-powered and self-adaptive motion sensor (UMS) is reported. Total mass of the UMS is less than 20 mg. Self-powered characteristic of the UMS is achieved based on the principle of triboelectric nanogenerator by using the coupling of triboelectrification and electrostatic induction as governed by the Maxwell's displacement current. Moreover, the UMS shows satisfactory self-adaptive performance of both temperature and humidity, less-sensitive to temperature in surroundings, from 15 ℃ to 60 ℃, and ambient humidity under 90% RH. Furthermore, sensing signals triggered by different motion behaviors, such as grasping, walking, stooping and so on, can be distinguished by the processor clearly, which can be applied to motion recognition and machine control. This work presents a novel UMS with characteristics of portability, energy conservation and environmental friendliness. The UMS shows broad prospect in perceptual layer application in IoT.
In order to achieve interaction and collaboration with humans, robots need to have the ability for tactile perception of simulating human. Traditional methods use electrically connected sensors with complex arrays, leading to intricate wiring, high manufacturing costs, and demanding current environments. A flexible sensor with simple structure, easy preparation process, and low cost based on triboluminescence effect is proposed in this paper, which avoids the complex array and wiring of traditional sensors. The study discusses the relationship between luminescent intensity and factors such as luminescent particle content, luminescent layer thickness, encapsulation layer thickness, and friction layer thickness. It also analyzes the mechanism of luminescence. A micro charge-coupled device is configured for the luminescent unit to collect optical information and is integrated with the robot's manipulator for testing. A simple sensing system is constructed to demonstrate environmental perception, acquiring, and feeding back shape and size information of contact objects in the dark. The system successfully identifies and judges target objects in complex dark environments, offering insights for applications such as unmanned assembly lines. It overcomes the challenge of intricate electrical connections, paving new avenues for intelligent object recognition research in human–computer interaction.
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