Abstract
Force/torque sensing on hand-held tools enables control of applied
forces, which is often essential in both tele-robotics and remote
guidance of people. However, existing force sensors are either bulky,
complex, or have insufficient load rating. This paper presents a novel
force sensing modality based on differential magnetic field readings in
a collection of sensor modules placed around a tool or device. The
instrumentation is easy to install and low profile, but nonetheless
achieves good performance. A detailed mathematical model and
optimization-based design procedure are also introduced. The modeling,
simulation, and optimization of the force sensor are described and then
used in the electrical and mechanical design and integration of the
sensor into an ultrasound probe. Through a neural network-based
nonlinear calibration, the sensor achieves average root-mean-square test
errors of 0.41 N and 0.027 Nm compared to an off-the-shelf ATI Nano25
sensor, which are 0.80% and 1.16% of the full-scale range
respectively. The sensor has an average noise power spectral density of
less than 0.0001 N/sqrt(Hz), and a 95% confidence interval resolution
of 0.063 N and 0.0086 Nm. The practical readout rate is 1.3 kHz over USB
serial and it can also operate over Bluetooth or Wi-Fi. This sensor can
enable instrumentation of manual tools to improve the performance and
transparency of teleoperated or autonomous systems.