Qin Lei

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mpeqinl@nus.edu.sg


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Now showing 1 - 3 of 3
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    Publication
    Soft robots based on dielectric elastomer actuators: A review
    (Smart Materials and Structures, 2019-09-04) UJJAVAL GUPTA; QIN LEI; WANG YUZHE; HAREESH GODABA; ZHU JIAN; MECHANICAL ENGINEERING; MATERIALS SCIENCE AND ENGINEERING
    Conventional robots are mainly made of rigid materials, such as steel and aluminum. Recently there has been a surge in the popularity of soft robots owing to their inherent compliance, strong adaptability and capability to work effectively in unstructured environments. Of the multitude of soft actuation technologies, dielectric elastomer actuators (DEAs), also nicknamed 'artificial muscles', exhibit fast response, large deformation and high energy density, and can simply be actuated with electric voltage. In this paper, we will discuss applications of DEAs to soft robots, including robotic grippers, terrestrial robots, underwater robots, aerial robots and humanoid robots. We will survey the state of the art regarding these interesting applications and outline the challenges and perspectives. As we know, there have been extensive studies on dielectric elastomer technology in the aspects of materials, mechanics, design, fabrication and controls. To enable practical applications, efforts are underway to decrease operational voltages, improve reliability, and impart new functionalities. Key challenges include the development of freestanding actuators, untethered operation, smart/electronics free actuators, solid and stretchable electrodes, miniaturization, combination of synergistic actuation technologies to impart novel functionalities, development of effective control strategies, etc. We hope that this review can facilitate and enhance applications of dielectric elastomer technology to soft robots.
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    Publication
    Deep Reinforcement Learning in Soft Viscoelastic Actuator of Dielectric Elastomer
    (IEEE ROBOTICS AND AUTOMATION LETTERS, 2019-02-11) LU LI; JUNNAN LI; QIN LEI; CAO JIAWEI; KANKANHALLI MOHAN S; ZHU JIAN; MECHANICAL ENGINEERING
    Dielectric elastomer actuators (DEAs) have been widely employed as artificial muscles in soft robots. Due to material viscoelasticity and nonlinear electromechanical coupling, it is challenging to accurately model a viscoelastic DEA, especially when the actuator is of a complex or irregular configuration. Control of DEAs is thus challenging but significant. In this letter, we propose a model-free method for control of DEAs, based on deep reinforcement learning. We perform dynamic feedback control by considering the time-dependent behavior of DEAs. Our method is generic in that it does not require task-specific knowledge about the structure or material parameters of the DEA. The experiments show that our method is robust to achieve accurate control for the DEAs of different configurations, different prestretches, and at different times (the material property usually changes due to viscoelasticity effects). To the best of our knowledge, this letter is the first effort to explore deep reinforcement learning for control of DEAs.
  • No Thumbnail Available
    Publication
    A Versatile Soft Crawling Robot with Rapid Locomotion
    (Soft Robotics, 2019-08-02) Qin Lei; LIANG XINQUAN; Hui Huang; Chui Chee Kong; ZHU JIAN; BIOMEDICAL ENGINEERING; MECHANICAL ENGINEERING
    This article presents a versatile soft crawling robot capable of rapid and effective locomotion. The robot mainly consists of two vacuum-actuated spring actuators and two electrostatic actuators. By programming the actuation sequences of different actuators, the robot is able to achieve two basic modes of locomotion: linear motion and turning. Subsequently, we have developed analytical models to interpret the static actuation performance of the robot body, including linear and bending motions. Moreover, an empirical dynamic model is also developed to optimize the locomotion speed in terms of frequency and duty cycle of the actuation signal. Furthermore, with the help of the strong electroadhesion force and fast response of the deformable body, the soft robot achieves a turning speed of 15.09°/s, which is one of the fastest among existing soft crawling robots to the best of our knowledge. In addition to the rapid and effective locomotion, the soft crawling robot can also achieve multiple impressive functions, including obstacle navigation in confined spaces, climbing a vertical wall with a speed of 6.67 mm/s (0.049 body length/s), carrying a payload of 69 times its self-weight on a horizontal surface, crossing over a 2 cm (0.15 body length) gap, and kicking a ball.