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Sheet metal parts with high-quality surface have wide applications in many manufacturing procedures. However, polishing these parts are challenging due to occurrence of deformations at contact area between the polishing tool and part. This stems from the thinness of these parts, making them susceptible to deformations, compared to thick solid parts. To address the above challenge, this study proposes a new robotic polishing path planing method that accounts for such deformations. The proposed method starts by estimating the contact area between the tool head, and the free-form surface of the sheet metal part is estimated using Hertz theory and differential geometry. Next, it uses a polynomial equation—that is derived from FEM-based contact analysis of the part—to calculate the true tool-part contact area under deformations. Then, it combines the contact-area information with a new constant speed robot path planing technique to ensure high-quality robot polishing. Numerical studies on several sample geometries verify the effectiveness of the method.

The application of abrasive suspension flow machining (ASFM) to grind a diesel engine injector nozzle is discussed in this paper. The purpose is to remove the sharp corners of the spray holes and improve the fuel flow through the injector nozzle. The proposed method adopts one-way flow to grind the spray holes for high-efficiency production. Compared with traditional reciprocating flow grinding methods using abrasive pastes, the viscosity of slurry and abrasive concentration of ASFM are lower, better for more smooth flow. To achieve a good grinding performance, it is important to determine proper viscosity and concentration. For this purpose, a design of experiments (DoE) method is adopted. In this paper, an orthogonal test method is combined with a non-linear regression method to optimize the process parameters. Through a range analysis on experiment results, the optimal process conditions in terms of the grinding efficiency and the grinding quality are determined. Experiment verifications show that the optimized process parameters can significantly improve the ASFM grinding efficiency and grinding quality.

This paper presents a new burr formation model for predicting drilling burr sizes in consideration of tool wear. A new force model is established by combining the drilling thrust force with the ploughing force caused by tool wear. The traditional drilling burr formation model is modified by using the new force model to determine burr heights and thicknesses in terms of tool wear percentage. A series of drilling experiments are carried out on two commonly used aerospace aluminiums to validate and calibrate the model. A close agreement between simulation and experiment is achieved showing that burr height and thickness increase with the increase in tool wear, and at 50% of tool wear, the maximum burr height could triple and the maximum burr thickness could double.

Surface electromyography (sEMG) is a promising technology that can capture muscle activation signals to control robots through novel human–machine interfaces (HMIs). This technology has already been applied in scenarios such as prosthetic design, assisted robot control, and rehabilitation training. This article provides an overview of sEMG-based robot control, covering two important aspects: (1) sEMG signal processing and classification methods and (2) robot control strategies and methods based on sEMG. First, the article outlines the general steps in sEMG signal processing and summarizes the commonly used methods for data acquisition, pre-processing, and feature extraction. In addition, machine-learning-based pattern recognition methods have been introduced for sEMG signal classification. Subsequently, user intent-based robot control strategies are classified into three categories: full-human continuous control, semi-autonomous continuous control, and discrete control, and their control methods and applicable scenarios are compared. Finally, this article discusses the advantages, disadvantages, and future development prospects of sEMG-based robot control. This review provides a comprehensive overview of sEMG-based robot control, from signal processing and classification methods to robot control strategies and methods, aiming to guide future research on selecting filters, feature sets, and pattern recognition methods and to assist in establishing sEMG-driven robot control frameworks.

The automated installation of hi-lok nuts by the robot is an effective way to replace tedious manual labor. For this purpose, an appropriate end-effector needs to be designed to carry out the feeding, alignment and fastening tasks. According to the installation process of hi-lok nuts, a motor driven fastening tool is designed with two parts: the front nut runner and rear driving shaft. The fastening task is modeled based on the force balances in the nut screwing action, which present the nut runner can rotate the nut as well as feed it axially. Then, a feeding-alignment (FA) device is designed to engage the nut feeding for fastening tool. The alignment action is modeled through the force balance about hi-lok nut involved with the nut gripper and nut runner. Finally, a tool end-effector has been built and integrated with an industrial robot. The successful implementation of automated installation of hi-lok nut demonstrates the effectiveness of the proposed installation method and the validation of the designed robotic end-effector.

The objective of this systematic review is to investigate the various approaches that have been undertaken in finite element analysis (FEA) of human–seat interactions and synthesize the existing knowledge. With advances in numerical simulation and digital human modeling, FEA has emerged as a powerful tool to study seating comfort and discomfort. FEA employs various biomechanical factors to predict the contact stress and pressure distribution in a particular seat design. Given the complexity of human–seat interaction, several modeling and processing steps are required to conduct realistic FEA. The steps of how to perform an FEA simulation on human–seat interactions, the different models used, the model mesh compositions, and the material properties are discussed and reviewed in this paper. This can be used as a guideline for future studies in the context of FEA of human–seat interactions.

The ongoing coronavirus pandemic requires more effective disinfection methods. Disinfection using ultraviolet light (UV), especially longer UVC wavelengths, such as 254 and 270/280 nm, has been proven to have virucidal properties, but its adverse effects on human skin and eyes limit its use to enclosed, unoccupied spaces. Several studies have shown the effectiveness of blue light (405 nm) against bacteria and fungi, but the virucidal property at 405 nm has not been much investigated. Based on previous studies, visible light mediates inactivation by absorbing the porphyrins and reacting with oxygen to produce reactive oxygen species (ROS). This causes oxidative damage to biomolecules, such as proteins, lipids, and nucleic acids, essential constituents of any virus. The virucidal potential of visible light has been speculated because the virus lacks porphyrins. This study demonstrated porphyrin-independent viral inactivation and conducted a comparative analysis of the effectiveness at 405 nm against other UVC wavelengths. The betacoronavirus 1 (strain OC43) was exposed to 405, 270/280, 254, and 222 nm, and its efficacy was determined using a median tissue culture infectious dose, i.e., TCID50. The results support the disinfection potential of visible light technology by providing a quantitative effect that can serve as the basic groundwork for future visible light inactivation technologies. In the future, blue light technology usage can be widened to hospitals, public places, aircraft cabins, and/or infectious laboratories for disinfection purposes.

In this study, we demonstrated a novel jumping robot that has the ability of accurate obstacle-crossing jumping and aerial pitch control. The novel robot can quickly leap high into the air with a powerful water jet thruster. The robot was designed to overcome multiple general obstacles via accurate jumping. Then a modified whale optimization algorithm (MWOA) was proposed to determine an optimized jumping trajectory according to the form of obstacles. By comparing with classical intelligent optimization algorithms, the MWOA revealed superiority in convergence rate and precision. Besides, the dynamics model of aerial pitch control was built and its effect was verified by the pitch control experiment. Lastly, the robot’s obstacle-crossing experiments were performed and the results validated the robot’s good ability of obstacle-crossing and aerial body righting. We believe the optimization of trajectory and the pitch control are of great help for the jumping robot’s complex jumping and obstacle-crossing performance.

Soft robotic fish have garnered attention for their compliance and adaptability. However, they remain vulnerable to mechanical damage, which limits their reliability. To address this vulnerability, we introduce a bio-inspired rigid–flexible coupled skin–scales system (BIS). The BIS integrates rigid scales with a flexible silicone substrate through a multi-stage molding process to enhance protection. Static compression tests demonstrate across five elastomers that the BIS enhances energy absorption capacity by at least 2.1 times compared to the purely flexible structure (PFS, silicone skin without scales). In robotic fish underwater experiments, BIS exhibits a tail-beat amplitude deviation of <10% relative to PFS and achieves 12.8 cm/s, retaining 87% of PFS’s peak speed. In addition, fluid dynamics simulations show BIS incurs only a minor drag in low-speed flow. By balancing protection and amplitude response, this research provides a practical approach for enhancing soft robotic fish in demanding aquatic environments.