In this study, a novel strain gauge arrangement and error reduction techniques were proposed to minimize crosstalk reading and simultaneously increase sensitivity on a decoupled six-axis force–moment (F/M) sensor. The calibration process that comprises the least squares method and error reduction techniques was implemented to obtain a robust decoupling matrix. A decoupling matrix is very crucial for minimizing error and crosstalk. A novel strain gauge arrangement that comprised double parallel strain gauges in the decoupled six-axis force–moment sensor was implemented to obtain high sensitivity. The experimental results revealed that the maximum calibration error, F/M sensor measurement error, and crosstalk readings were reduced to 3.91%, 1.78%, and 4.78%, respectively.
In this study, a novel six-axis force/moment (F/M) sensor was developed. The sensor has a novel ring structure comprising a cross-beam elastic body with sliding and rotating mechanisms to achieve complete decoupling. The unique sliding and rotating mechanisms can reduce cross-talk effects caused by minimized structural interconnection. The forces Fx, Fy, and Fz and moments Mx, My, and Mz can be measured for the six-axis F/M sensors according to the elastic deformation of strain gauges attached to the cross beam. Herein, we provide detailed descriptions of the mathematical models, model idealizations, model creation, and the mechanical decoupling principle. The paper also presents a theoretical analysis of the strain based on Timoshenko beam theory and the subsequent validation of the analysis results through a comparison of the results with those obtained from a numerical analysis conducted using finite element analysis simulations. The sensor was subjected to experimental testing to obtain the maximum cross-talk errors along the following six axes under different loadings (the errors are presented in parentheses): Fx under SMy (2.12%), Fy under SMx (1.88%), Fz under SMz (2.02%), Mx under SFz (1.15%), My under SFx (1.80%), and Mz under SFx (2.63%). The proposed sensor demonstrated a considerably improved cross-talk error performance compared with existing force sensors.
Strain gage type six-axis force/moment (F/M) sensors have been largely studied and implemented in industrial applications by using an external data acquisition board (DAQ). The use of external DAQs will ill-affect accuracy and crosstalk due to the possibility of voltage drop through the wire length. The most recent research incorporated DAQ within a relatively small F/M sensor, but only for sensors of the capacitance and optical types. This research establishes the integration of a high-efficiency DAQ on six-axis F/M sensor with a revolutionary arrangement of 32 strain gages. The updated structural design was optimized using the sequential quadratic programming method and validated using Finite Element Analysis (FEA). A new, integrated DAQ system was designed, tested, and compared to commercial DAQ systems. The proposed six-axis F/M sensor was examined with the calibrated jig. The results show that the measurement error and crosstalk have been significantly reduced to 1.15% and 0.68%, respectively, the best published combination at this moment.
Research on robot trajectory correction on a curved surface has seen a surge in the last two decades to deal with issues in many machining processes. Due to the intricacies involved in complex machining, the real-time correction of robot end-effector position and orientation is highly challenging. The existing approaches are either computationally expensive or inadequate for high accuracy in desired trajectory tracking. Hence, this research explores and implements a novel sophisticated approach, barring minor complications, to empower industrial robots to adjust poses in real-time automatically. In contrast with other studies, the proposed technique does not require any prior geometric information of the workpiece, such as a CAD model or a 3D scan. Our proposed technique relies solely on force/torque sensor feedback information obtained from a 6-axis force/torque sensor installed at the end-effector. When the developed tool comes in contact with the curved surface, the force sensor transmits the data to the pose correction algorithm. The pose correction algorithm estimates the adjustment required to make the tool normal to the surface. The effectiveness and feasibility of the proposed scheme were validated through numerous experiments carried out with a 6-DOF industrial robot. The final results of the curved surface trajectory correction demonstrates that the contact-based robot pose correction has significantly improved. The estimated average error on depth (Z-axis), and angles (Rx,Ry) are 0.7 mm, 0.7 • , and 0.9 • , respectively.
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