Shijian Luo’s research while affiliated with Zhejiang University and other places

We present VR-Doh, a hands-on 3D modeling system designed for creating and manipulating elastoplastic objects in virtual reality (VR). The system employs the Material Point Method (MPM) for simulating realistic large deformations and incorporates optimized Gaussian Splatting for seamless rendering. With direct, hand-based interactions, users can naturally sculpt, deform, and edit objects interactively. To achieve real-time performance, we developed localized simulation techniques, optimized collision handling, and separated appearance and physical representations, ensuring smooth and responsive user interaction. The system supports both freeform creation and precise adjustments, catering to diverse modeling tasks. A user study involving novice and experienced users highlights the system's intuitive design, immersive feedback, and creative potential. Compared to traditional geometry-based modeling tools, our approach offers improved accessibility and natural interaction in specific contexts.

In order to study the cutting performance of the straight edge hob and reduce the cutting power consumption model of the straight edge hob, this paper takes the cutting power of the straight edge hob as the minimum goal, and establishes the mathematical model of the optimization design of the straight edge hob based on the composite optimization method. The mathematical model is solved by MATLAB software. At the same time,the mowing characteristics of a roller blade were studied by investigating the relationship between the hob and the coordination of variables such as rotational speed and roller diameter with the mowing parameters. The parameter analysis of straight edge hob before and after structural parameter optimization is generated, and a design method is proposed based on this. After defining the objective function and constraint conditions, the influence of structural parameters on the power consumption and efficiency of the hob was determined by optimising the complex method; this could significantly adjust the hob parameters to lower its power consumption. The energy consumption of the optimized design is reduced by 11.1 % compared with the original scheme, and the optimization effect is remarkable. The results show that the best working parameters of the hob are cutting speed of 1000 r/min, sliding cutting angle and grinding edge angle of 25~30°. Moreover, practical tests demonstrated the feasibility of using the proposed method to design the straight edge hob to improve mowing performance and hob stability. This study can provide parameter foundation and an optimization method for lowering chopping power consumption of the roller mower blade.

Advances in computer image recognition have significantly impacted many industries, including healthcare, security and autonomous systems. This paper aims to explore the potential of improving image algorithms to enhance computer image recognition. Specifically, we will focus on regression methods as a means to improve the accuracy and efficiency of identifying images. In this study, we will analyze various regression techniques and their applications in computer image recognition, as well as the resulting performance improvements through detailed examples and data analysis. This paper deals with the problems related to visual image processing in outdoor unstructured environment. Finally, the heterogeneous patterns are converted into the same pattern, and the heterogeneous patterns are extracted from the fusion features of data modes. The simulation results show that the perception ability and recognition ability of outdoor image recognition in complex environment are improved.

In this study, an attempt was made to interpolate linear models to approximate an entire nonlinear system, based on the traditional theory of fuzzy PID control. This approach considered the discrepancies between current detection and linear modeling, in conjunction with variations in motor current and the laws governing trajectory motion. The difference at a specific operating point between the obtained linear model and the actual nonlinear system was integrated into the linear system. Subsequently, a fuzzy controller was introduced for hall data within the cascade PID controller loop to synthesize a state feedback controller. Thereafter, variations in motor current were managed through fuzzy PID control. The theory, initially based on a single-wheel ramp scenario, was generalized to adapt to operational control on a general bump ramp. This method demonstrated satisfactory tracking responses upon testing. The paper also discusses the application of PID control in linear systems and how intelligent control, through its nonlinear approximation capabilities, addresses complex issues. However, the algorithms of intelligent control are often computationally intensive and structurally complex, making them impractical for real-world applications. In light of the nonlinear characteristics of certain systems, where accurate mathematical models are unattainable, the features of nonlinear PID control are advantageous for systems with low model accuracy. This scheme exhibits robust anti-interference capabilities and effectively enhances system control precision. Nevertheless, it has been noted to have a slower tracking speed for input signals. To evaluate the efficacy of fuzzy control, a tool capable of real-time positioning of the mobile robot was employed. The optimization design of the fuzzy PID controller was based on variations in motor current. Under different conditions, tests and observations were conducted, and the proposed fuzzy control method provided a favorable tracking response. The actual test outcomes were also effective, offering a novel perspective for the control of path stability.

This study aims to examine design students’ intention towards using Artificial Intelligence-aided Design Tools (AIDTs). An extended model is developed by combining the affective-cognitive consistency theory with the Unified Theory of Acceptance and Use of Technology (UTAUT). Data are collected through online comments from Chinese streaming media platforms and responses from a survey involving 313 Chinese students, with subsequent analysis using Partial Least Squares and Structure Equation Modeling (PLS-SEM) statistical techniques and Natural Language Processing (NLP). The results reveal that technophobia, perceived enjoyment, performance expectancy, and effort expectancy directly affect the intention of design students to use AIDTs. Additionally, social influence, facilitating conditions, and subjective knowledge indirectly influence this intention. Technophobia, perceived enjoyment, and subjective knowledge emerge as critical determinants. The proposed framework offers insights for AIDTs developers to enhance user experience, while educators are encouraged to provide requisite training and incentives to motivate design student’s engagement with AIDTs.