Air-Chamber Based Soft Six-Axis Force/Torque Sensor for Human-Robot Interaction
Jun Huo, Hongge Ru, Bo Yang, Xingjian Chen, Xi Li, Jian Huang
- Year
- 2025
- Access
- Open access
Abstract
Soft multi-axis force/torque sensors provide safe and precise force interaction. Capturing the complete degree-of-freedom of force is imperative for accurate force measurement with six-axis force/torque sensors. However, cross-axis coupling can lead to calibration issues and decreased accuracy. In this instance, developing a soft and accurate six-axis sensor is a challenging task. In this paper, a soft air-chamber type six-axis force/torque sensor with 16-channel barometers is introduced, which housed in hyper-elastic air chambers made of silicone rubber. Additionally, an effective decoupling method is proposed, based on a rigid-soft hierarchical structure, which reduces the six-axis decoupling problem to two three-axis decoupling problems. Finite element model simulation and experiments demonstrate the compatibility of the proposed approach with reality. The prototype's sensing performance is quantitatively measured in terms of static load response, dynamic load response and dynamic response characteristic. It possesses a measuring range of 50 N force and 1 Nm torque, and the average deviation, repeatability, non-linearity and hysteresis are 4.9$\%$, 2.7$\%$, 5.8$\%$ and 6.7$\%$, respectively. The results indicate that the prototype exhibits satisfactory sensing performance while maintaining its softness due to the presence of soft air chambers.
Keywords
Related papers
Review and perspectives on multimodal perception, mutual cognition, and embodied execution for human–robot collaboration in Industry 5.0
Kai Ding, Qingyuan Mao, Yaqian Zhang +3 more
Robotics and Computer-Integrated Manufacturing · 2026
Towards human-centric manufacturing: Task planning under uncertainties in human–robot collaborative assembly
Yingchao You, Ze Ji, Changyun Wei
Robotics and Computer-Integrated Manufacturing · 2026
Agentic HRC: Achieving context alignment via memory for Human–Robot Collaboration
Jiahui Si, Wenchao Li, Xi Chen +4 more
Robotics and Computer-Integrated Manufacturing · 2026
Adaptive Physics-informed Transformer with Gaussian process residual compensation for inverse dynamics modeling in Human–Robot Collaboration
Rui Qian, Xi Zhang, Dongpeng Li +2 more
Robotics and Computer-Integrated Manufacturing · 2026