Sarah Bergbreiter

This report provides a summary of the outcomes of the Interdisciplinary Workshop on Mechanical Intelligence held in 2024. Mechanical Intelligence (MI) represents the phenomenon that novel structural features of material/biological/robotic systems can encode intelligence through responsiveness, adaptivity, memory, and learning in the mechanical structure itself. This is in contrast to computational intelligence, wherein the intelligence functions occur through electrical signaling and computer code. The two-day workshop was held at NSF headquarters on May 30-31 and included 38 invited academic researcher participants, and 8 program officers from the NSF. The workshop was structured around active small and large group discussions in groups of 4-5 and 9-10 with the goal of addressing topical questions on MI. Working groups entered notes into shared presentation slides for each discussion session and presented their outcomes in a final presentation on the last day. Here we summarize the overall outcomes of the workshop.

This report provides a summary of the outcomes of the Interdisciplinary Workshop on Mechanical Intelligence held in 2024. Mechanical Intelligence (MI) represents the phenomenon that novel structural features of material/biological/robotic systems can encode intelligence through responsiveness, adaptivity, memory, and learning in the mechanical structure itself. This is in contrast to computational intelligence, wherein the intelligence functions occur through electrical signaling and computer code. The two-day workshop was held at NSF headquarters on May 30-31 and included 38 invited academic researcher participants, and 8 program officers from the NSF. The workshop was structured around active small and large group discussions in groups of 4-5 and 9-10 with the goal of addressing topical questions on MI. Working groups entered notes into shared presentation slides for each discussion session and presented their outcomes in a final presentation on the last day. Here we summarize the overall outcomes of the workshop.

Scaling the design of robots up or down remains a fundamental challenge. While biological systems follow well-established isometric and allometric scaling laws relating mass, stride frequency, velocity, and torque, it is unclear how these relationships translate to robotic systems. In this paper, we generate similar allometric scaling laws for bipedal robots across three orders of magnitude in leg length. First, we conduct a review of legged robots from the literature and extract empirical relationships between leg length (L), body length, mass, and speed. These data show that robot mass scales more closely to L^2, in contrast to the L^3 scaling predicted by isometric scaling. We then perform controlled simulation studies in Drake using three variants of real quasi-passive, hip-actuated walkers with different foot geometries and control strategies. We evaluate the performance of each design scaled with leg length, L. Across all robots, walking velocity follows the expected L^(1/2) trend from dynamic similarity. Minimum required torque scales more closely with m*L than the isometric model of m*L^2. Foot geometry scaled proportionally with L^1. These results provide new insight into how robot designs allometrically scale to different sizes, and how that scaling is different from isometric or biological scaling laws.

Scaling the design of robots up or down remains a fundamental challenge. While biological systems follow well-established isometric and allometric scaling laws relating mass, stride frequency, velocity, and torque, it is unclear how these relationships translate to robotic systems. In this paper, we generate similar allometric scaling laws for bipedal robots across three orders of magnitude in leg length. First, we conduct a review of legged robots from the literature and extract empirical relationships between leg length (L), body length, mass, and speed. These data show that robot mass scales more closely to L^2, in contrast to the L^3 scaling predicted by isometric scaling. We then perform controlled simulation studies in Drake using three variants of real quasi-passive, hip-actuated walkers with different foot geometries and control strategies. We evaluate the performance of each design scaled with leg length, L. Across all robots, walking velocity follows the expected L^(1/2) trend from dynamic similarity. Minimum required torque scales more closely with m*L than the isometric model of m*L^2. Foot geometry scaled proportionally with L^1. These results provide new insight into how robot designs allometrically scale to different sizes, and how that scaling is different from isometric or biological scaling laws.

Sensors made from soft polymer composites help intelligent systems become more functional and robust, enabling new applications in which conventional rigid devices may be unsuitable. Although soft sensors have been well studied under quasi-static loading conditions, their performance and effect of sensor transduction under large-amplitude strains (≥10%) at higher frequencies (≥10 Hz) have been less explored. We carried out a comprehensive study of both piezoresistive and capacitive strain sensors made using polydimethylsiloxane (PDMS) and carbon nanotube-doped PDMS. The effects of viscoelastic stress relaxation on the sensors' responses were evaluated and captured using a generalized Maxwell model, which was then used to predict higher frequency mechanical behaviors. The sensors were then characterized under uniaxial tensile loads with three load amplitudes and 11 frequencies ranging from 0.01 to 40 Hz. Our results revealed that capacitive sensing is less sensitive to both loading conditions compared to resistive sensing due to its dependence on changing sensor geometry instead of the electromechanical properties of the soft polymer composite. New results from dynamic loads over 10 Hz also provide evidence to support previous hypotheses regarding the nonlinear behaviors of soft piezoresistive sensors. We expect these findings can serve as a framework for improved deployment of soft sensors in more dynamic robotic systems.

As environmental disasters happen more frequently and severely, seeking the source of pollutants or harmful particulates using plume tracking becomes even more important. Plume tracking on small quadrotors would allow these systems to operate around humans and fly in more confined spaces, but can be challenging due to poor sensitivity and long response times from gas sensors that fit on small quadrotors. In this work, we present an approach to complement chemical plume tracking with airflow source-seeking behavior using a custom flow sensor that can sense both airflow magnitude and direction on small quadrotors < 100 g. We use this sensor to implement a modified version of the `Cast and Surge' algorithm that takes advantage of flow direction sensing to find and navigate towards flow sources. A series of characterization experiments verified that the system can detect airflow while in flight and reorient the quadrotor toward the airflow. Several trials with random starting locations and orientations were used to show that our source-seeking algorithm can reliably find a flow source. This work aims to provide a foundation for future platforms that can use flow sensors in concert with other sensors to enable richer plume tracking data collection and source-seeking.

Physical scaling laws predict that miniaturizing robotic mechanisms should enable exceptional robot performance in metrics such as speed and precision. Although these scaling laws have been explored in a variety of microsystems, the benefits and limitations of downscaling three-dimensional (3D) robotic mechanisms have yet to be assessed because of limitations in microscale 3D manufacturing. In this work, we used the Delta robot as a case study for these scaling laws. We present two sizes of 3D-printed Delta robots, the microDeltas, measuring 1.4 and 0.7 millimeters in height, which demonstrate state-of-the-art performance in both size and speed compared with previously reported Delta robots. Printing with two-photon polymerization and subsequent metallization enabled the miniaturization of these 3D robotic parallel mechanisms integrated with electrostatic actuators for achieving high bandwidths. The smallest microDelta was able to operate at more than 1000 hertz and achieved precisions of less than 1 micrometer by taking advantage of its small size. The microDelta's relatively high output power was demonstrated with the launch of a small projectile, highlighting the utility of miniaturized robotic systems for applications ranging from manufacturing to haptics.

Aquatic robots can improve their state estimation and control by measuring relative water flow for tasks such as calculating speed, local currents, or wakes. This paper presents a novel aquatic whisker-inspired flow sensor for accurate flow speed and direction prediction. Our sensor design addresses common waterproofing and corrosion issues through a magnetic transduction approach that isolates the Hall effect sensor and electronics from the aquatic environment. Flow-induced drag on a whisker element rotates an attached magnet, which is detected from the submerged waterproof Hall effect sensor. This design also provides modularity of the whisker drag element, and we demonstrate how changing the whisker profile can affect the sensor’s sensitivity and range. Finally, using both analytical and experimental models, we selected a sensor design to demonstrate the velocity measurement of a small, remote-controlled boat. The sensors predicted the boat’s velocity with a root mean square error of 0.08ms<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−1</sup>, highlighting the potential of this sensor design for future aquatic robot applications.

The concept of micrometer-scale swimming robots, also known as microswimmers, navigating the human body to perform robotic tasks has captured the public imagination and inspired researchers through its numerous representations in popular media. This attention highlights the enormous interest in and potential of this technology for biomedical applications, such as cargo delivery, diagnostics, and minimally invasive surgery, as well as for applications in microfluidics and manufacturing. To achieve the collective behavior and control required for microswimmers to effectively perform such actions within complex, in vivo and microfluidic environments, they must meet a strict set of engineering criteria. These requirements include, but are not limited to, small size, structural monodispersity, flexibility, biocompatibility, and multifunctionality. Additionally, microswimmers must be able to adapt to delicate environments, such as human vasculature, while safely performing preprogrammed tasks in response to chemical and mechanical signals. Naturally information-bearing biopolymers, such as peptides, RNA, and DNA, can provide programmability, multifunctionality, and nanometer-scale precision for manufactured structures. In particular, DNA is a useful engineering material because of its predictable and well-characterized material properties, as well as its biocompatibility. Moreover, recent advances in DNA nanotechnology have enabled unprecedented abilities to engineer DNA nanostructures with tunable mechanics and responsiveness at nano- and micrometer scales. Incorporating DNA nanostructures as subcomponents in microswimmer systems can grant these structures enhanced deformability, reconfigurability, and responsiveness to biochemical signals while maintaining their biocompatibility, providing a versatile pathway for building programmable, multifunctional micro- and nanoscale machines with robotic capabilities. In this Account, we highlight our recent progress toward the experimental realization of responsive microswimmers made with compliant DNA components. We present a hybrid top-down, bottom-up fabrication method that combines templated assembly with structural DNA nanotechnology to address the manufacturing limitations of flexibly linked microswimmers. Using this method, we construct microswimmers with enhanced structural complexity and more controlled particle placement, spacing, and size, while maintaining the compliance of their DNA linkage. We also present a novel experimental platform that utilizes two-photon polymerization (TPP) to fabricate millimeter-scale swimmers (milliswimmers) with fully customizable shapes and integrated flexible linkers. This platform addresses limitations related to population-level heterogeneity in micrometer-scale systems, allowing us to isolate the effects of milliswimmer designs from variations in their physical dimensions. Using this platform, we interrogate established hydrodynamic models of microswimmer locomotion and explore how design and actuation parameters influence milliswimmer velocity. We next explore opportunities for enhancing microswimmer responsiveness, functionality, and physical intelligence through the inclusion of nucleic acid subcomponents. Finally, we highlight how our parallel research on xeno nucleic acids and interfacing DNA nanotechnology with living cells can enable the creation of fully organic, truly biocompatible microswimmers with enhanced functionality, improving the viability of microswimmers for applications in healthcare, manufacturing, and synthetic biology.

Miniaturizing legged robot platforms is challenging due to hardware limitations that constrain the number, power density, and precision of actuators at that size. By leveraging design principles of quasi-passive walking robots at any scale, stable locomotion and steering can be achieved with simple mechanisms and open-loop control. Here, we present the design and control of “Zippy”, the smallest self-contained bipedal walking robot at only 3.6 cm tall. Zippy has rounded feet, a single motor without feedback control, and is capable of turning, skipping, and ascending steps. At its fastest pace, the robot achieves a forward walking speed of 25 cm/s, which is 10 leg lengths per second, the fastest biped robot of any size by that metric. This work explores the design and performance of the robot and compares it to similar dynamic walking robots at larger scales.

Microswimmers are sub-millimeter swimming robots that show potential as a platform for controllable locomotion in applications, including targeted cargo delivery and minimally invasive surgery. To be viable for these target applications, microswimmers will eventually need to be able to navigate environments with dynamic fluid flows and forces. Experimental studies with microswimmers towards this goal are currently rare because of the difficulty of isolating intentional microswimmer locomotion from environment-induced motion. In this work, we present a method for measuring microswimmer locomotion within a complex flow environment using fiducial microspheres. By tracking the particle motion of ferromagnetic and non-magnetic polystyrene fiducial microspheres, we capture the effect of fluid flow and magnetic field gradients on microswimmer trajectories. We then determine the field-driven translation of these microswimmers relative to fluid flow and demonstrate the effectiveness of this method by illustrating the motion of multiple microswimmers through different flows.

As environmental disasters happen more frequently and severely, seeking the source of pollutants or harmful particulates using plume tracking becomes even more important. Plume tracking on small quadrotors would allow these systems to operate around humans and fly in more confined spaces, but can be challenging due to poor sensitivity and long response times from gas sensors that fit on small quadrotors. In this work, we present an approach to complement chemical plume tracking with airflow source-seeking behavior using a custom flow sensor that can sense both airflow magnitude and direction on small quadrotors (< 100 g). We use this sensor to implement a modified version of the ‘Cast and Surge’ algorithm that takes advantage of flow direction sensing to find and navigate towards flow sources. A series of characterization experiments verified that the system can detect airflow while in flight and reorient the quadrotor toward the airflow. Several trials with random starting locations and orientations were used to show that our source-seeking algorithm can reliably find a flow source. This work aims to provide a foundation for future platforms that can use flow sensors in concert with other sensors to enable richer plume tracking data collection and source-seeking.

Miniaturizing legged robot platforms is challenging due to hardware limitations that constrain the number, power density, and precision of actuators at that size. By leveraging design principles of quasi-passive walking robots at any scale, stable locomotion and steering can be achieved with simple mechanisms and open-loop control. Here, we present the design and control of "Zippy", the smallest self-contained bipedal walking robot at only 3.6 cm tall. Zippy has rounded feet, a single motor without feedback control, and is capable of turning, skipping, and ascending steps. At its fastest pace, the robot achieves a forward walking speed of 25 cm/s, which is 10 leg lengths per second, the fastest biped robot of any size by that metric. This work explores the design and performance of the robot and compares it to similar dynamic walking robots at larger scales.

Abstract Active colloids are modular assemblies of distinct micro‐ and nanoscale components that can perform complex robotic tasks. While recent advances in templated assembly methods enable high‐throughput fabrication of multi‐material active colloids, their limitations reduce the ability to construct flexibly linked colloidal systems, restricting their complexity, agility, and functionality. Here, templated assembly by selective removal (TASR) is leveraged to construct multicomponent colloidal microstructures that are connected with compliant DNA nanotube linkages. Polycarbonate heat (PCH) molding is employed to create high‐surface‐energy templates for improved polystyrene microsphere assembly via TASR. This increase in template surface energy improves microsphere assembly by more than 100‐fold for two‐sphere microstructures. An inverse relationship between microstructure complexity (i.e., the number of microspheres) and assembly yields is observed. PCH‐assisted TASR is leveraged to construct larger colloidal structures containing up to 26 microspheres, multi‐sphere microrotors, and structurally homogeneous populations of flexibly linked, two‐sphere microswimmers that locomote in fluid environments. Real‐time modification of a microswimmer is also demonstrated through nuclease‐mediated degradation of the DNA linkages, highlighting the DNA‐enabled reconfiguration and responsiveness capabilities of these microswimmers. These results establish PCH‐assisted TASR as a versatile method for constructing flexibly linked, modular microrobots with controlled geometry, enhanced agility, and dynamic response.

Microswimmers are sub-millimeter swimming microrobots that show potential as a platform for controllable locomotion in applications including targeted cargo delivery and minimally invasive surgery. To be viable for these target applications, microswimmers will eventually need to be able to navigate in environments with dynamic fluid flows and forces. Experimental studies with microswimmers towards this goal are currently rare because of the difficulty isolating intentional microswimmer motion from environment-induced motion. In this work, we present a method for measuring microswimmer locomotion within a complex flow environment using fiducial microspheres. By tracking the particle motion of ferromagnetic and non-magnetic polystyrene fiducial microspheres, we capture the effect of fluid flow and field gradients on microswimmer trajectories. We then determine the field-driven translation of these microswimmers relative to fluid flow and demonstrate the effectiveness of this method by illustrating the motion of multiple microswimmers through different flows.

This study presents the development, characterization, and demonstration of a tunable substrate for small jumping robots. Jumping robots in the literature are typically evaluated when jumping from rigid surfaces, in contrast to surfaces with more significant compliance or damping that are encountered in the natural world. The aim of this work is to create a physical substrate, or ’ground', for which the effective mass, compliance, and damping can be programmed. This system enables quick testing of various substrate conditions and also allows for the introduction of complex nonlinearities to analyze the interactions between latch-mediated spring actuation (LaMSA) systems and their environment. A mathematical model for the substrate is defined and the system is built with a fast brushless DC motor and controller running on a real-time target machine. The results illustrate the range of compliance and damping that can be achieved, as well as example jumps from the substrate using a 4 g jumper and a 108 g jumping robot.

Systems in nature are stochastic as well as nonlinear. In traditional applications, engineered filters aim to minimize the stochastic effects caused by process and measurement noise. Conversely, a previous study showed that the process noise can reveal the observability of a system that was initially categorized as unobservable when deterministic tools were used. In this paper, we develop a stochastic framework to explore observability analysis and sensor placement. This framework allows for direct studies of the effects of stochasticity on optimal sensor placement and selection to improve filter error covariance. Numerical results are presented for sensor selection that optimizes stochastic empirical observability in a bioinspired setting.

Dynamic and agile locomotion in legged robots enables them to overcome obstacles and navigate complex and unstructured terrain. However, the leg mechanisms and actuators needed for versatile locomotion are much more challenging to manufacture and integrate in sub‐gram scale robots. Herein, Picotaur, a 15.4 mg hexapedal robot with legs that enable various locomotion tasks such as turning, climbing 3D‐printed stairs, and pushing loads for the first time at these size scales, is presented. 3D printing with two‐photon polymerization enables the manufacture of electrostatically driven 2 degrees of freedom legs on a robot body made from a flexible printed circuit board. Based on simple control inputs, Picotaur can achieve alternating tripod gaits, reaching speeds up to 57 mm (7.2 body lengths) per second, as well as pronking gaits to tackle a wider variety of terrain. This approach to manufacturing and controlling legged robots at smaller scales provides a path forward toward robots that can be used for practical applications ranging from inspection to exploration and rival the performance of insects at similar size scales.

Understanding airflow around a drone is critical for performing advanced maneuvers while maintaining flight stability. Recent research has worked to understand this flow by employing 2D and 3D flow sensors to measure flow from a single source like wind or the drone's relative motion. Our current work advances flow detection by introducing a strategy to distinguish between two flow sources applied simultaneously from different directions. By densely packing an array of flow sensors (or whiskers), we alter the path of airflow as it moves through the array. We have named this technique ``flow shadowing'' because we take advantage of the fact that a downstream whisker shadowed (or occluded) by an upstream whisker receives less incident flow. We show that this relationship is predictable for two whiskers based on the percent of occlusion. We then show that a 2x2 spatial array of whiskers responds asymmetrically when multiple flow sources from different headings are applied to the array. This asymmetry is direction-dependent, allowing us to predict the headings of flow from two different sources, like wind and a drone's relative motion.

This work introduces a new microscale g-switch designed to activate at a specific acceleration threshold.The switch is fabricated on lightweight PET film and directly 3D printed using two-photon polymerization, then metalized through sputter deposition.The first contact of the switch was confirmed by manually displacing the proof mass until continuity was observed with a contact resistance of 7 .The force required to make electrical contact was tested to determine the equivalent g-force required to activate the sensor.This force occurred at 250 N resulting in an acceleration threshold of 157,000g for this proof mass and gap.

Desert locusts possess an array of setae that function as aerodynamic sensors for flight stabilization.Using a similar sensing approach would be beneficial in ensuring a stable flight for microaerial vehicles, however implementation of current sensors is limited by size, information latency, and fabrication processes.This work focuses on the design and manufacturing of small bio-inspired airflow sensors to fulfill this role.This work introduces sensors that produce digital signals when subjected to a specific airflow threshold.The sensors are fabricated using a 3D printing microfabrication technique known as two-photon polymerization.This rapid manufacturing process allowed the fast production of sensors of varying flow sensitivity.The fabricated sensors showed high sensitivity to airflows below 5 m/s, and display behaviors like setae do in nature.

Understanding airflow around a drone is critical for performing advanced maneuvers while maintaining flight stability. Recent research has worked to understand this flow by employing 2D and 3D flow sensors to measure flow from a single source like wind or the drone’s relative motion. Our current work advances flow detection by introducing a strategy to distinguish between two flow sources applied simultaneously from different directions. By densely packing an array of flow sensors (or whiskers), we alter the path of airflow as it moves through the array. We have named this technique “flow shadowing” because we take advantage of the fact that a downstream whisker shadowed (or occluded) by an upstream whisker receives less incident flow. We show that this relationship is predictable for two whiskers based on the percent of occlusion. We then show that a 2x2 spatial array of whiskers responds asymmetrically when multiple flow sources from different headings are applied to the array. This asymmetry is direction-dependent, allowing us to predict the headings of flow from two different sources, like wind and a drone’s relative motion.

In this work, we present a thin-film shape memory alloy microactuator with a magnetic spring. This novel actuator design utilizes two permanent magnets and 3D-printed magnet holders to effectively apply a tensile strain on the NiTi thin-film. This actuator is expected to generate 8.7 mN of blocking force, and a free displacement of 30 µm is experimentally characterized. The actuator leverages bare NiTi film (∼ 1 µm thick) for actuation, enabling a high actuator bandwidth up to 50 Hz. A comprehensive analytical model is also studied, which was then validated by comparing to the experimental results. A launcher mechanism was designed and integrated with the NiTi actuator, and this mechanism was used to launch a microscale projectile (a salt grain) thereby demonstrating the relative high power actuation achievable with thin-film NiTi.

Insects, bats, and small birds show outstanding flight performance even under complex atmospheric conditions, which is partially due to the ability of these natural fliers to sense and react to disturbances quickly. These biological systems often use large numbers of sensors arrayed across their bodies to detect disturbances, but previous efforts to use large arrays of sensors in engineered fliers have typically resulted in slow responses due to the need to scan and process data from the large number of sensors. To address the challenges of capturing disturbances in a large sensing array with low latency, this work proposes and demonstrates a modular soft sensing system to quickly detect disturbances in small unmanned aerial vehicles. A large array of soft strain sensors with high sensing resolution covers the entire wingspan, providing rich information on wing deformation. Owing to the modular design, decentralized computation enables the sensing system to efficiently manage sensor data, resulting in sufficiently fast sampling to capture wing dynamics while all 32 sensors embedded in the modular soft sensing skin are used. This hardware architecture also results in significantly reduced noise in the sensing system, leading to a high signal-to-noise ratio. These methods can ultimately enable fast and reliable control of both soft and rigid robotic systems using large arrays of soft sensors.

Our ability to measure and image biology at small scales has been transformative for developing a new generation of insect-scale robots. Because of their presence in almost all environments known to humans, insects have inspired many small-scale flying, swimming, crawling, and jumping robots. This inspiration has affected all aspects of the robots’ design, ranging from gait specification, materials properties, and mechanism design to sensing, actuation, control, and collective behavior schemes. This article highlights how insects have inspired a new class of small and ultrafast robots and mechanisms. These new robots can circumvent motors’ force-velocity tradeoffs and achieve high-acceleration jumping, launching, and striking through latch-mediated spring-actuated (LaMSA) movement strategies. In the article, we apply a solution-driven bioinspired design framework to highlight the process for developing LaMSA-inspired robots and systems, starting with understanding the key biological themes, abstracting them to solution-neutral principles, and implementing such principles into engineered systems. Throughout the article, we emphasize the roles of modeling, fabrication, materials, and integration in developing bioinspired LaMSA systems and identify critical future enablers such as integrative design approaches. Graphical abstract

Many small insects are agile fliers that exhibit remarkable disturbance rejection properties, while conversely, small unmanned aircraft systems (sUAS) traditionally perform poorly when faced with environmental uncertainties. This work presents a bio-inspired sensing method where a suite of custom made, soft, capacitive strain sensors are distributed along the underside of the wing of a fixed-wing sUAS. Measurements from these sensors during outdoor flight testing are analyzed through linear and nonlinear artificial neural networks (ANN) to show that certain dynamical states are encoded within the distributed measurements. Furthermore, it is shown that spatial filtering of distributed strain data results in a significant signal-to-noise-ratio reduction in estimated signals. This work holds great potential in the field of sensing and control for agile flight and disturbance rejection.

Abstract Room‐temperature eutectic Gallium Indium (eGaIn)‐based devices offer stretchable, conductive, and reconfigurable properties for robotics, communications, and medicine. Microfluidics enables eGaIn device creation, but these typically have larger feature sizes. Recent three‐dimensional (3D) printing advancements, particularly direct laser writing (DLW), allow for sub‐100 µm microfluidic devices. However, interfacing DLW microfluidics with larger systems poses challenges in channel resist removal, eGaIn filling, and electrical integration, limiting micro‐scale liquid metal device application. This study introduces a multiscale, cost‐effective, three‐step process combining DLW‐fluidic microchannels with centimeter‐scale substrates made via stereolithography (SLA). It establishes a robust interface between independently printed materials and simplifies eGaIn filling in microfluidic channels as small as 50 µm, potentially enabling smaller liquid metal features. The research also presents eGaIn coils with 43–770 mΩ resistance and 2–4 nH inductance. This process facilitates low‐temperature, conductive, flexible interfaces for sensors, actuators, and circuits, and expands the range for size‐dependent properties of passive electronic components like resistors, capacitors, and inductors from liquid metal.

We present the design and experimental results of the first 1-DOF, hip-actuated bipedal robot. While passive dynamic walking is simple by nature, many existing bipeds inspired by this form of walking are complex in control, mechanical design, or both. Our design using only two rigid bodies connected by a single motor aims to enable exploration of walking at smaller sizes where more complex designs cannot be constructed. The walker, “Mugatu”, is self-contained and autonomous, open-loop stable over a range of input parameters, able to stop and start from standing, and able to control its heading left and right. We analyze the mechanical design and distill down a set of design rules that enable these behaviors. Experimental evaluations measure speed, energy consumption, and steering.

Systems in nature are stochastic as well as nonlinear. In traditional applications, engineered filters aim to minimize the stochastic effects caused by process and measurement noise. Conversely, a previous study showed that the process noise can reveal the observability of a system that was initially categorized as unobservable when deterministic tools were used. In this paper, we develop a stochastic framework to explore observability analysis and sensor placement. This framework allows for direct studies of the effects of stochasticity on optimal sensor placement and selection to improve filter error covariance. Numerical results are presented for sensor selection that optimizes stochastic empirical observability in a bioinspired setting.

The designs of origami-and kirigami-inspired robots enable configurations from 2D to 3D shapes, lightweight systems, and take advantage of rapid fabrication techniques. These features have been explored for robotics in applications ranging from aerospace to medical devices. However, achieving reversible reconfigurations that sustain/lock between shapes without requiring constant energy input and allow system integration (e.g., sensing, assembly) is challenging. This letter proposes a design and fabrication approach that uses electrically driven mechanisms to enable reversible self-reconfiguration and locking without constant energy input. We leverage origami and kirigami-inspired designs to transmit the motions of a planar artificial muscle and low melting point alloys for time-controlled locking. Using these techniques, we demonstrate compact systems in multiple reconfigurable robotic applications, from gripping to crawling.

Abstract Small jumping robots can use springs to maximize jump performance, but they are typically not able to control the height of each jump owing to design constraints. This study explores the use of the jumper’s latch, the component that mediates the release of energy stored in the spring, as a tool for controlling jumps. A reduced-order model that considers the dynamics of the actuator pulling the latch and the effect of spring force on the latch is presented. This model is then validated using high speed video and ground reaction force measurements from a 4 g jumper. Both the model and experimental results demonstrate that jump performance in small insect-inspired resource-constrained robots can be tuned to a range of outputs using latch mediation, despite starting with a fixed spring potential energy. For a fixed set of input voltages to the latch actuator, the results also show that a jumper with a larger latch radius has greater tunability. However, this greater tunability comes with a trade-off in maximum performance. Finally, we define a new metric, ‘Tunability Range,’ to capture the range of controllable jump behaviors that a jumper with a fixed spring compression can attain given a set of control inputs (i.e. latch actuation voltage) to choose from.

We present the design and experimental results of the first 1-DOF, hip-actuated bipedal robot. While passive dynamic walking is simple by nature, many existing bipeds inspired by this form of walking are complex in control, mechanical design, or both. Our design using only two rigid bodies connected by a single motor aims to enable exploration of walking at smaller sizes where more complex designs cannot be constructed. The walker, "Mugatu", is self-contained and autonomous, open-loop stable over a range of input parameters, able to stop and start from standing, and able to control its heading left and right. We analyze the mechanical design and distill down a set of design rules that enable these behaviors. Experimental evaluations measure speed, energy consumption, and steering.

Abstract Developing small‐scale, lightweight, and flexible devices with integrated microactuators is one of the critical challenges in wearable haptic devices, soft robotics, and microrobotics. In this study, a novel fabrication process that leverages the benefits of 3D printing with two‐photon polymerization and flexible printed circuit boards (FPCBs) is presented. This method enables flexible microsystems with 3D‐printed electrostatic microactuators, which are demonstrated in a flexible integrated micromirror array and a legged microrobot with a mass of 4 mg. 3D electrostatic actuators on FPCBs are robust enough to actuate the micromirrors while the device is deformed, and they are easily integrated with off‐the‐shelf electronics. The crawling robot is one of the lightest legged microrobots actuated without external fields, and the legs actuated with 3D electrostatic actuators enable a locomotion speed of 0.27 body length per second. The proposed fabrication framework opens up a pathway toward a variety of highly integrated flexible microsystems.

This research develops a novel sensor for aquatic robots inspired by the whiskers of harbor seals. This sensor can detect the movement of water, offering valuable data on speed, currents, barriers, and water disturbance. It employs a mechano-magnetic system, separating the whisker-like drag part from the electronic section, enhancing water resistance and durability. The flexible design allows customizing the drag component's shape for different uses. The study uses an analytical model to examine the sensor's capabilities, including aspects such as shape, cross-sectional area, ratio, and immersion depth of the whisker part. It also explores the effects of design on Vortex-Induced Vibrations (VIVs), a key focus in the study of biological and robotic aquatic whiskers. The sensor's practical use was tested on a remote-controlled boat, showing its proficiency in estimating water flow speed. This development has enormous potential to enhance navigation and perception for aquatic robots in various applications.

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.

Creating microscale actuated mechanisms in 3D space is extremely challenging due to limitations in microfabrication processes. In this work, we present a 3D-printed adaptive microgripper that is driven by thin-film NiTi microactuators with 3D-printed linkage mechanisms. The microgripper's fingers are passively adaptive so that the microgripper can provide conformal gripping on 3D objects. The microgripper can move its fingers by <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{225}\ \boldsymbol{\mu} \mathbf{m}$</tex> and apply a blocking force of <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{30}\ \boldsymbol{\mu} \mathbf{N}$</tex> per one finger when 20 mA was applied to the NiTi actuators. The microgripper was also integrated onto a printed circuit board with a current regulating circuit and a 9 V battery. Since the NiTi actuator requires a low voltage for actuation, the microgripper could be integrated with simple and affordable electronics. The fully integrated microgripper system was demonstrated playing with a shape sorting box at the microscale for the first time.

Robots that use impulsive mechanisms to achieve high-speed and high-powered motion are becoming more common and better understood, but control of these systems remains relatively rudimentary. Among robots that use spring actuation to generate motion, robot actuation and mechanisms are usually not controlled intentionally in order to achieve variation in the system's behavior, or they are controlled only roughly via adjustments made to the amount of energy stored in the mechanism. We describe the development, construction, and test of an impulsive catapult mechanism whose design is inspired by the grasshopper leg and for which extensive variation in the projectile trajectory is achieved by force control of the actuator that restrains the spring. As a step toward future controlled jumping robots, we give a detailed model of this system, validate this model experimentally, and explain how the actuator dynamics are critical to our ability to vary the system's trajectory using this approach. This work represents a novel approach to the control of spring actuated robots and illustrates how they can be controlled even under highly limiting actuator constraints.

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.