%0 Journal Article %J IEEE Sensors Journal %D 2016 %T Self-Assembling, Low-Cost, and Modular mm-Scale Force Sensor %A Joshua B. Gafford %A Wood, Robert J. %A Conor J Walsh %X

The innovation in surgical robotics has seen a shift toward flexible systems that can access remote locations inside the body. However, a general reliance on the conventional fabrication techniques ultimately limits the complexity and the sophistication of the distal implementations of such systems, and poses a barrier to further innovation and widespread adoption. In this paper, we present a novel, self-assembling force sensor manufactured using a composite lamination fabrication process, wherein linkages pre-machined in the laminate provide the required degrees-of-freedom and fold patterns to facilitate self-assembly. Using the purely 2-D fabrication techniques, the energy contained within a planar elastic biasing element directly integrated into the laminate is released post-fabrication, allowing the sensor to self-assemble into its final 3-D shape. The sensors are batch-fabricated, further driving down the production costs. The transduction mechanism relies on the principle of light intensity modulation, which allows the sensor to detect axial forces with millinewton-level resolution. The geometry of the sensor was selected based on the size constraints inherent in minimally invasive surgery, as well as with a specific focus on optimizing the sensor's linearity. The sensor is unique from the fiber-based force sensors in that the emitter and the detector are encapsulated within the sensor itself. The bare sensor operates over a force range of 0-200 mN, with a sensitivity of 5 V/N and a resolution of 0.8 mN. The experimental results show that the sensor's stiffness can be tuned using a thicker material for the spring layer and/or encapsulation/integration with soft materials. The empirical validation shows that the sensor has the sensitivity and the resolution necessary to discern the biologically relevant forces in a simulated cannulation task.

%B IEEE Sensors Journal %V 16 %P 69-76. [Cover Article] %8 1 Jan 2016 %G eng %U http://dx.doi.org/10.1109/JSEN.2015.2476368 %N 1