Strain wave gears are widely used as reducers in robots, including collaborative and industrial robots. As a key component, they play a crucial role in determining overall robot performance. To enhance their effectiveness, various studies have focused on directly measuring the performance of assemblies or predicting the performance of individual components through analysis. However, there is a notable lack of research that experimentally measures and compares the physical properties of the circular spline, flexspline, and wave generator—the primary elements of strain wave gears. In this paper, we developed equipment to measure the radial stiffness of the flexspline, one of the key components, and validated its reliability through preliminary experiments. Furthermore, we measured and compared the radial stiffness of flexsplines produced by three different manufacturers. These findings are expected to provide valuable insights for improving the performance of strain wave gears and advancing robotics technology.

In this study, a module combining various types of sensors was developed to increase search efficiency inside collapsed buildings. It was designed to be less than 70 mm in diameter so that it can be put into narrow spaces, and is equipped with a small & high-performance processor to process multiple sensor data. To increase sensor data processing efficiency, multi thread based software was configured, and the images were combined and transmitted to ensure time synchronization of multi-channel video data. A human detection function based on sound source detection using two microphones was implemented. The developed multi-sensor module was tested for operation by mounting it on a snake-type robot in a test bed simulating a disaster site. It was confirmed that the visible range of the robot to which the multi-sensor module was applied was expanded, and the ability to detect human and low-light human detect was secured.

It is challenging to automate the shoe upper adhesive spraying process using a robot due to the three-dimensional curved shape of the shoe upper. This paper proposes a method to automate the shoe upper adhesive spraying process with a 3-D measuring device and an industrial robot. The adhesive spraying automation process consists of the following steps, First, a transformation matrix calibration is performed to make the points measured by the 3-D measuring device and the robot end-effector points the same. Second, the shoe gauge line that connects the shoe adhesive spaying line measured by the 3D measurement device is smoothed. Lastly, the target points of the robot end-effector to quantitatively spray the adhesive are selected and the robot end-effector position/orientation to operate the robot is generated. The proposed method was validated on the test bed of a shoe upper spray system. With the method proposed in this paper, even non-robot experts can measure shoe gauge line data with a 3-D measuring device and the shoe upper adhesive spraying process can be automated without manually operating a robot.