Acoustic transmission, or sound, can effectively communicate information over distances through various media. We focus on generating acoustic transmission using pneumatically driven resonators for wireless tactile sensing without the need for any electronics at the end-effector or contact point. We explore the relationship between emitted frequency and the geometry of the resonance chamber. When a normal compressive force is applied to the end cap, the compliant resonant cavity deforms, leading to an increase in frequency measurable by an external microphone. Prior work uses tube resonators with fipple attachments. In the present work, we study whether a different smaller audible cylindrical resonator with air blown across the entryway can be utilized instead. We test the utility of the Helmholtz resonator model in predicting the experimental frequency response. Resonance is often modeled for rigid cavities, presenting unique challenges in predicting resonance for the design of soft resonating taxels.

The disposal of waste electrical and electronic equipment (WEEE) presents a sustainability challenge, particularly for waste printed circuit boards (PCBs). PCBs are challenging to sort out from other waste materials in part because traditional industrial end-effectors struggle to reliably grip these irregularly shaped objects with unmodeled surface-mounted components. Vision-based separators, while effective for object categorization, face challenges with identifying precise grasp points on PCB surfaces. This paper studies regrasping control to enhance suction cup grasping performance on PCBs, addressing issues arising from uneven surfaces and intricate features that interfere with suction sealing. We categorize PCBs into two recycling levels – with large surface features intact or removed – and conduct experiments on both stationary and conveyor belt setups with realistic vision-based grasp planners. Results show that jumping regrasping improves pick-and-place success rate. Haptically driven jumping – using the Smart Suction Cup – is especially useful for unprocessed waste PCBs with large surface mount parts. The proposed method offers a promising solution to enhance the efficiency and reliability of robotic grasping in recycling applications.

The Smart Suction Cup is a tactile sensing and gripping system designed to enhance pick-and-place operations in industrial settings. While previous research has primarily focused on utilizing this technology for haptic search in cases of initial grasp failure, this study introduces a novel application: following contours. This function is already established as an important function for object recognition and grasp planning – substantiated by numerous works using other tactile sensors. Here, we explore contour following for a flow-based tactile sensor because it is not susceptible to visual occlusions nor tactile sensor wear. Experimental validation demonstrates the Smart Suction Cup’s ability to track edges at different speeds and navigate various planar contours, showcasing rapid and robust tracking of edges. Notably, the Smart Suction Cup can reliably operate at a speed of 3 cm/s. This is one step towards the adoption of the Smart Suction Cup for real-world applications.

Suction cups are an important gripper type in industrial robot applications, and the prior literature focuses on using vision-based planners to improve grasping success in these tasks. Vision-based planners can fail due to adversarial objects or lose generalizability for unseen scenarios, without retraining learned algorithms. In this article, we propose haptic exploration to improve suction cup grasping when visual grasp planners fail. We present the smart suction cup, an end effector that utilizes internal flow measurements for tactile sensing. We show that model-based haptic search methods, guided by these flow measurements, improve grasping success by up to 2.5× as compared with using only a vision planner during a bin-picking task. In characterizing the smart suction cup on both geometric edges and curves, we find that flow rate can accurately predict the ideal motion direction even with large postural errors. The smart suction cup includes no electronics on the cup itself, such that the design is easy to fabricate and haptic exploration does not damage the sensor. This work motivates the use of suction cups with autonomous haptic search capabilities in especially adversarial scenarios.

The Dorsal Grasper, an assistive wearable grasping device, incorporates supernumerary fingers and an artificial palm with the forearm and back of the hand, respectively. It enables power wrap grasping and adduction pinching with its V-shaped soft fingers. Designed with C6/C7 spinal cord injury in mind, it takes advantage of active wrist extension that remains in this population after injury. We propose that allowing the operator to actively participate in applying grasp forces on the object, using the back of the hand, enables intuitive, fast and reliable grasping relevant for the execution of activities of daily living. Functional grasping is tested in three normative subjects and a person with C6 SCI using the Grasp and Release Test. Results indicate that this device provides promising performance on a subset of objects that complements the existing compensatory strategies used by people with C6/C7 SCI. We find that the addition of the artificial palm is important for increasing maximum grip strength, by increasing contact friction and protecting the opisthenar.

We predict the progression of Immunoglobulin A Nephropathy using three classification methods: Classification and Regression Trees, Logistic Regression, and Feed-Forward Artificial Neural Networks. We treat it as a classification problem, of predicting progression to end-stage renal disease in the ten years following initial diagnosis. We compared classifier performance using ROC analysis. All three methods yielded good classifiers, with AUC between 0.85 and 0.95. The results were generally in-line with expectations, with poor kidney performance on presentation, and evident macroscopic and microscopic damage, all associated with poorer prognosis.