The motion performance of humanoid robots has not yet fully reached the level of human beings, which is one of the factors hindering their large-scale industrial application. This limitation stems not only from constraints in control algorithms but also from mechanical structure design, particularly the leg configuration, which largely determines a robot’s dynamic balance, load capacity, and energy efficiency. The study examined the origins and evolution of leg configurations in humanoid robots, both domestically and internationally. Currently, the leg configurations of humanoid robots are primarily categorized into three types: serial, parallel, and hybrid serial-parallel. Their structural characteristics directly influence locomotion performance. The study compared the serial, the parallel and the series-parallel configurations and their performance characteristics. The serial configuration offers a large workspace and high flexibility, but its relatively lower stiffness—due to the extended joint transmission chain—compromises its load capacity. The parallel configuration provides high rigidity and fast dynamic response, yet its range of motion is limited. The hybrid serial-parallel design combines the strengths of both, achieving balanced stiffness and flexibility, which has increasingly made it a key research focus in recent years. Finally, this paper also discussed technical difficulties and hot spots in the study of leg configuration and pointed out the development trend: the leg configuration is developing from single series configuration to parallel and series-parallel configuration, from rigid actuator to elastic actuator and quasi direct drive actuator, from torque control to hybrid force-position control.

Plastic gears have many unique advantages, and have been widely used in smart household, automobile and various fields, domestic and foreign researchers have carried out many studies on the structural design, material characteristics and performances of plastic gears, and formed some standards. A brief overview of the history of plastic gears was given, and the most recent advancements in plastic gear research were presented. These included the pros and cons of plastic gears, creative profile and structure designs, material modifications and applications, injection molding process optimization, new measurement techniques, performance testing and evaluation, and the creation of plastic gear standardization. It’s concluded that plastic gear is at an important stage of development, comprehensive performance improvement by new structure design and material applications well as carrying out more deep experimental researches to accurately grasp their behavior and performance are the directions of future plastic gear researches.

Traditional defect detection algorithms exhibit poor performance in accurately detecting complex dark spots on the surface of plastic gears. There are three primary issues: firstly, inaccurately distinguishing the size and position of dark spots on the gear edge; secondly, a high rate of missed detection for light dark spots; thirdly, a tendency to misjudge the point gate as dark spots. This paper proposed an improved detection method for complex dark spots on plastic gears based on U-Net++ and feature fusion. The dark spot area was predicted through U-Net++ and corrected depending on gradient features. Multi-feature fusion analysis was utilized to provide the final judgment result, thus improving the accuracy and stability of complex dark spot detection. The test results demonstrate that the P_c value, which represents the accuracy of the detection results, is as high as 98.93%, and the average value of IoU, representing the accuracy of the segmentation results, reaches 0.864. In comparison to traditional defect detection algorithms and uncorrected deep learning algorithms, the proposed method increases the average value of IoU by 0.478 and 0.309, respectively.

A reducer is a typical hysteresis system, and the hysteresis affects its transmission performance. The existing hysteresis models of reducers usually ignore the hysteresis characteristics of geometric errors and treat them as constants, which results in the inability of these models to fully reflect the hysteresis characteristics of reducers. In order to better understand the mechanism behind gear reducer hysteresis, this paper theoretically analyzes the effects of friction, elastic deformation, and geometric errors on the phenomenon. Additionally, it develops a new model for gear reducer hysteresis that takes geometric error hysteresis characteristics into account. The model's practical application reveals the dynamic characteristics of the lost motion in the reducer, and a dynamic lost motion formula is deduced. Experimental research verifies the influence of geometric errors on the reducer hysteresis and confirms the effectiveness of the hysteresis model. By changing the loading rate during the lost motion test, the dynamic characteristics of the lost motion are verified. It was found that different materials have different effects on the loading rate. For every 0.05 (N·m)/s increase in the loading rate, the lost motion test results of the small metal gear reducer and the small plastic gear reducer with a modulus of 0.22 mm decrease by about 3′ and 10′, respectively.