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Advancements in bulk metallic glass thermoplastic forming unleash the potential to fabricate microscale metallic features with unparalleled precision and durability, i.e. microspine gripping structures for mobility platforms on planetary or in-space robots. Four designs of grippers were fabricated and rigorously tested. Coefficient of friction on four test surfaces were measured and compared to SiC paper and Velcro. The hardness and elasticity of the bulk metallic glasses make them a game-changer in the field, offering a superior alternative to conventional nonmetallic grippers. • Microspine grippers were manufactured via thermoplastic forming of bulk metallic glasses using silicon-on-insulator molds. • The microspines excelled on textured surfaces, where sharp points anchor on to pores or softer regions. • Mechanical behavior of microspines were studied using nanoindentor-based micro-compression and computer simulations. [ABSTRACT FROM AUTHOR]

Rigid-flex circuit boards are becoming more prevalent as the limits are pushed on the size, mass, and geometry of electronic systems. A key aspect of designing a rigid-flex printed circuit boards (PCB) system is an assessment of the dynamic properties of the PCB and predicting system performance under dynamic loading. Among current modeling methodologies for rigid-flex PCB, a simplified modeling methodology that adequately captures the system dynamics does not exist. This article presents a novel, computationally efficient approach for modeling rigid-flex PCB systems and the calibration of the material models via modal testing. The resulting simplified model is able to capture system frequencies, mode shapes, and representative force-displacement behavior. The proposed methodology is used to model NASA Jet Propulsion Laboratory's Pop-Up Flat Folding Explorer Robot (PUFFER) and assess the sensitivity of a system model to input parameters. [ABSTRACT FROM AUTHOR]

Tactile sensing is an instrumental modality of robotic manipulation, as it provides information that is not accessible via remote sensors such as cameras or lidars. Touch is particularly crucial in unstructured environments, where the robot's internal representation of manipulated objects is uncertain. In this study we present the sensorization of an existing artificial hand, with the aim to achieve fine control of robotic limbs and perception of object's physical properties. Tactile feedback is conveyed by means of a soft sensor integrated at the fingertip of a robotic hand. The sensor consists of an optical fiber, housing Fiber Bragg Gratings (FBGs) transducers, embedded into a soft polymeric material integrated on a rigid hand. Through several tasks involving grasps of different objects in various conditions, the ability of the system to acquire information is assessed. Results show that a classifier based on the sensor outputs of the robotic hand is capable of accurately detecting both size and rigidity of the operated objects (99.36 and 100% accuracy, respectively). Furthermore, the outputs provide evidence of the ability to grab fragile objects without breakage or slippage e and to perform dynamic manipulative tasks, that involve the adaptation of fingers position based on the grasped objects' condition. [ABSTRACT FROM AUTHOR]