BiModal Hemispherical Sensor: A Unifying Solution for Three Axis Force and Contact Angle Measurement In robotic tasks that require physical interactions such as manipulation and legged locomotion, it is important to simultaneously measure contact forces and contact angles. This paper presents a unified solution for simultaneously measuring three axis contact forces and contact angles for legged locomotion or manipulation. Unlike most tactile sensors, the presented design utilizes the stress field method by sampling pressures over multiple locations within an elastomer, enabling inherently robust operation against impact and abrasive interactions. The presented sensor is designed for pointfeet quadrupedal robots and can be easily scaled down for other applications such as grasping. The sampled stress distribution is mapped to output forces f_x, f_y, and f_mathrmz and two contact angles, theta and psi on the hemispherical sensor surface via Gaussian process regression. The prototype sensor is able track normal and shear forces accurately, achieving a normalized root mean (RMS) squared error of only 1.00%xe2x80x931.36% for f_mathrmz across multiple tests with up to 180N normal force, and a normalized RMS error of 1.71%xe2x80x934.67% and 1.82%xe2x80x936.68% for f x  and f y , respectively, with up to 80N shear force. Additionally, the footpad is able to estimate the contact location coordinates theta and psi with a normalized RMS error of 2.69%xe2x88x927.51% over a range of 040mathrmo and 2.79%xe2x80x939.62% over a range of 030mathrmo, respectively. The footpad can estimate contact location over a maximum range of thetapm 450 and psipm 45mathrmo, and can withstand over 450N of normal force at location theta psi 0mathrmo without reaching saturation. This prototype demonstrates the ability to simultaneously measure force in three axes and contact angles using Gaussian process regression, with the potential to explore other regression methods for embedded computing and miniaturization of the design for finger tip scale sensors.

Development of a 3axis Human Fingertip Tactile Sensor with an OrthoPlanar Spring Human experts have mastered many manual skills. Transferring those skills to robots or human novices is challenging. Not only the movements, but also the exerted forces are of importance. In this paper we propose a sensor that can measure the force vector acting on the human fingertip, without covering the part of the fingertip that is contact with the touched object. Compared to our previous iterations of this sensor, we use a spring instead of viscoelastic material as the deformable material for the sensor. While it is challenging to include a spring in the given form factor, springs have the benefit of lower hysteresis than viscoelastic materials. This paper presents the integration of the spring in the sensor and shows experimental validation with 8 subjects. Compared to our previous version of the sensor with 2 Hall effect sensors, we achieved improved sensing characteristics.