A 3D-Force and Torsion Sensor Using Patterned Color Encoding

Current multi-axis force sensors often rely on complex mechanical structures or arrays of discrete transducers, resulting in larger footprints, higher complexity, and limited scalability for compact applications such as robotic fingertips or wearable tactile interfaces. To address these limitations, this paper introduces a novel optical sensing approach that uses a top-layer patterned color surface and an array of color sensors to decouple and measure normal, shear, and torsional forces within a highly compact 15 × 15 mm footprint. The patterned surface functions as a visual encoding layer, where applied forces induce measurable, direction-dependent shifts in reflected color distribution. By deploying multiple color sensors in an array, each sensor captures localized color variations, enabling spatial reconstruction of both magnitude and direction of applied loads through differential color analysis. The sensor's performance was validated through robotic gripper integration, where it successfully provided multi-axis force feedback and enabled adaptive gripping force adjustment to achieve robust and stable object manipulation. The experimental results confirm the system's ability to effectively sensing 3D forces and torsion forces, and support closed-loop control in adaptive robotic grasping. This design presents a scalable, low-profile alternative to conventional multi-axis force sensors, suitable for integration into space-constrained robotic and haptic systems.