Whisker-based tactile sensors have the potential to perform fast and accurate 3D mappings of the environment, complementing vision-based methods under conditions of glare, reflection, proximity, and occlusion. However, current algorithms for mapping with whiskers make assumptions about the conditions of contact, and these assumptions are not always valid and can cause significant sensing errors. Here we introduce a new whisker sensing system with a tapered, flexible whisker. The system provides inputs to two separate algorithms for estimating radial contact distance on a whisker. Using a Gradient-Moment (GM) algorithm, we correctly detect contact distance in most cases (within 4% of the whisker length). We introduce the Z-Dissimilarity score as a new metric that quantifies uncertainty in the radial contact distance estimate using both the GM algorithm and a Moment-Force (MF) algorithm that exploits the tapered whisker design. Combining the two algorithms ultimately results in contact distance estimates more robust than either algorithm alone.

Flapping wing micro aerial vehicles face challenges in sensing and reacting to disturbances like wind gusts. This work introduces a new microscale bio-inspired digital strain sensor to detect these perturbations. The sensor is designed to change logic states when a specified strain threshold has been reached. The sensors are 3D printed on a flexible Mylar wing using two-photon polymerization. Three digital sensors with varying strain thresholds demonstrate differences in activation timing due to different design parameters. The sensors are tested at the 25 Hz flapping frequency of a hawkmoth, an insect with comparable wing size. A perturbation was added to the flapping wing by subjecting it to a 3 m/s wind gust. A single digital sensor is able to identify the wind disturbance by comparing the time of the first strain threshold crossing. A separate approach looks at the change in sensor ‘on’-time for each flap cycle and provides a clear indication of the wind disturbance.

Moths use hundreds of strain sensors (campaniform sensilla) on each wing to quickly respond to perturbations that may otherwise destabilize the moth during flight. A similar sensing approach could help stabilize micro-aerial vehicles (MAVs), but large sensor arrays are challenging due to the wiring and large latency that exists when capturing data from many traditional strain sensors. This work introduces a simplified bio-inspired strain sensor; the sensor interface and kinematics were inspired by campaniform sensilla that output a spike only in response to signals of interest. The engineered sensor outputs a discrete analog signal representing strain thresholds. A kinematic model of the sensor design is developed and describes the measured strain in terms of the sensor’s geometric parameters. This model is used to understand trade-offs between sensor resolution and range, and is validated using a finite element model (FEM) of the sensor. The sensor was designed with ease of fabrication in mind, using simple techniques and commercially available components. Fabricated sensors were tested in a four-point flexural test, and the data from the analytical and FEM model show good agreement with the experimental results. The sensors demonstrate resolutions of 83, 158, and 281 microstrain for the different designs tested. A sensor is placed on a model wing to illustrate future applications to MAVs as well as the sensor’s ability to sense both compressive and tensile strains.