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This paper introduces a compact, non-contact joint torque sensor that uses an array of photo-reflectors to measure micro-deformations in an elastic structure. To improve sensitivity and noise reduction, the sensor employs a redundant arrangement of photo-reflectors and a quadratic-programming-based calibration method. Experimental results demonstrate improved torque measurement accuracy and resolution compared to current-sensor-based methods, validated through motor-level torque and admittance control.
By optically measuring micro-deformations with redundant photo-reflectors and quadratic programming calibration, this joint torque sensor achieves 2.14x better resolution than least-squares calibration, enabling more precise low-torque control.
This study proposes a non-contact photo-reflector-based joint torque sensor for precise joint-level torque control and safe physical interaction. Current-sensor-based torque estimation in many collaborative robots suffers from poor low-torque accuracy due to gearbox stiction/friction and current-torque nonlinearity, especially near static conditions. The proposed sensor optically measures micro-deformation of an elastic structure and employs a redundant array of photo-reflectors arranged in four directions to improve sensitivity and signal-to-noise ratio. We further present a quadratic-programming-based calibration method that exploits redundancy to suppress noise and enhance resolution compared to least-squares calibration. The sensor is implemented in a compact form factor (96 mm diameter, 12 mm thickness). Experiments demonstrate a maximum error of 0.083%FS and an RMS error of 0.0266 Nm for z-axis torque measurement. Calibration tests show that the proposed calibration achieves a 3 sigma resolution of 0.0224 Nm at 1 kHz without filtering, corresponding to a 2.14 times improvement over the least-squares baseline. Temperature chamber characterization and rational fitting based compensation mitigate zero drift induced by MCU self heating and motor heat. Motor-level validation via torque control and admittance control confirms improved low torque tracking and disturbance robustness relative to current-sensor-based control.