Temperature Compensation Method of Six-Axis Force/Torque Sensor Using Gated Recurrent Unit

This study aims to enhance the accuracy of a six-axis force/torque sensor compared to existing approaches that utilize Multi-Layer Perceptron (MLP) and the Least Square Method. The sensor used in this study is based on a photo-coupler and operates with infrared light, making it susceptible to dark current effects, which cause drift due to temperature variations. Additionally, the sensor is compact and lightweight (45g), resulting in a low thermal capacity. Consequently, even small amounts of heat can induce rapid temperature changes, affecting the sensor's performance in real time. To address these challenges, this study compares the conventional MLP approach with the proposed Gated Recurrent Unit (GRU)-based method. Experimental results demonstrate that the GRU approach, leveraging sequential data, achieves superior performance.

Parameter Optimization of Optical Six-Axis Force/Torque Sensor for Legged Robots

This paper introduces a novel six-axis force/torque sensor tailored for compact and lightweight legged robots. Unlike traditional strain gauge-based sensors, the proposed non-contact design employs photocouplers, enhancing resistance to physical impacts and reducing damage risk. This approach simplifies manufacturing, lowers costs, and meets the demands of legged robots by combining small size, light weight, and a wide force measurement range. A methodology for optimizing sensor parameters is also presented, focusing on maximizing sensitivity and minimizing error. Precise modeling and analysis of objective functions enabled the derivation of optimal design parameters. The sensor's performance was validated through extensive testing and integration into quadruped robots, demonstrating alignment with theoretical modeling. The sensor's precise measurement capabilities make it suitable for diverse robotic environments, particularly in analyzing interactions between robot feet and the ground. This innovation addresses existing sensor limitations while contributing to advancements in robotics and sensor technology, paving the way for future applications in robotic systems.