Robert J. Wood

Autonomous robotic-assisted surgery (RAS) has emerged as a promising objective in biomedical technology, further enhanced by miniaturization toward microrobotic-assisted surgery (μ-RAS). This reduction in scale promises minimally invasive, partially or fully automated surgical procedures, with the potential to reduce patient recovery times, lower medical costs, and enable previously unavailable procedural options. This perspective highlights the specific advances in RAS that potentially map to the microscale (μ-RAS), organized across five surgical domains: endovascular, endoluminal, laparoscopic, ophthalmic, and orthopedic. We examine both clinical demands and technological advances in surgical robotics and identify the key innovations required for progress across these surgical fields. Our contribution is distinct in combining the perspectives of both surgical experts and bioengineering innovators, outlining a roadmap for the advancement and eventual integration of autonomous RAS and μ-RAS into mainstream surgical practice.

We introduce an additive approach for the design of a class of transformable structures based on two-bar linkages ("scissor mechanisms") joined at vertices to form a two-dimensional mesh which we call a pantograph lattice. Our approach shows how these lattices unfold from a one-dimensional collapsed state to two-dimensional surfaces of single and double curvature. We provide an algorithm for growing pantograph structures that allows us to explore the full space of possible mechanisms, and we use it to computationally design and physically assemble a series of examples of varying complexity. We finally demonstrate a streamlined method for automated fabrication of pantograph lattices using multimaterial 3D printing.

Active 3D reconstruction of moving objects requires selecting informative viewpoints while accounting for object motion uncertainty during the decision-to-execution delay. Existing methods address only parts of this problem: next-best-view (NBV) planners for object reconstruction typically optimize surface coverage but assume static objects, while motion-aware active perception for moving targets accounts for target motion but prioritizes tracking or visibility over reconstruction coverage. This work presents a motion-uncertainty-aware NBV framework for reconstructing an unknown rigid object undergoing planar motion, using noisy planar position measurements of the object and depth observations from a mobile robot. The key idea is to evaluate each candidate viewpoint by its expected observation quality over plausible future object states induced by motion and measurement uncertainty, rather than at a single predicted object pose. To obtain this predictive belief, a fixed-lag Gaussian Process smoother estimates and predicts the object state from noisy position measurements. The resulting belief is used to generate candidate viewpoints around the predicted object location, filter them by reachability, and estimate their expected coverage-driven scores. Simulation and real-world experiments demonstrate improved reconstruction completeness over non-predictive NBV and prediction-only tracking methods, bridging coverage-driven active reconstruction and prediction-driven tracking.

Active 3D reconstruction of moving objects requires selecting informative viewpoints while accounting for object motion uncertainty during the decision-to-execution delay. Existing methods address only parts of this problem: next-best-view (NBV) planners for object reconstruction typically optimize surface coverage but assume static objects, while motion-aware active perception for moving targets accounts for target motion but prioritizes tracking or visibility over reconstruction coverage. This work presents a motion-uncertainty-aware NBV framework for reconstructing an unknown rigid object undergoing planar motion, using noisy planar position measurements of the object and depth observations from a mobile robot. The key idea is to evaluate each candidate viewpoint by its expected observation quality over plausible future object states induced by motion and measurement uncertainty, rather than at a single predicted object pose. To obtain this predictive belief, a fixed-lag Gaussian Process smoother estimates and predicts the object state from noisy position measurements. The resulting belief is used to generate candidate viewpoints around the predicted object location, filter them by reachability, and estimate their expected coverage-driven scores. Simulation and real-world experiments demonstrate improved reconstruction completeness over non-predictive NBV and prediction-only tracking methods, bridging coverage-driven active reconstruction and prediction-driven tracking.

Abstract Soft grippers, used in applications such as food handling and assistive devices, leverage multiple soft fluidic actuators (SFAs) for safe and compliant grasping. Designing SFAs is challenging because they must satisfy multiple functional requirements while operating outside the principles of rigid machine design, as they undergo large deformations and exhibit material nonlinearity. Because fabricating numerous design candidates is costly, computational tools have emerged to expedite the search for optimal designs. However, existing computational tools do not focus on SFA design optimization for state-specific grasping, where actuators are optimized for a particular deformation dictated by the intended use case. Moreover, many existing tools support a limited range of performance metrics and optimization modes. Here, we present PneuGrasp, an open-source tool for the design optimization of SFAs according to a user-specified grasping task. The tool can analyze design candidates across multi-functional combinations of seven performance metrics, including the understudied metrics of grasping force, actuation speed, and actuation energy. In addition, PneuGrasp supports three optimization modes that together provide parameter intuition and shorten optimization time. Through a series of examples evaluating over 1000 design candidates, we demonstrate that PneuGrasp can identify optimized designs that outperform our baseline. For instance, one design achieved a 60% reduction in maximum strain and a 52% reduction in actuation volume, while another showed a 405% decrease in a combined durability–grasping–force performance score. We fabricated and tested over 30 actuators across five distinct designs, demonstrating PneuGrasp’s relative prediction capabilities. PneuGrasp can be found online.

Abstract Robust millimeter-scale mechanisms have the potential to enable a new generation of end effectors for minimally invasive procedures, aiding surgeons in performing complex tasks with improved precision, repeatability, and dexterity. Despite ongoing advances in fabrication methods, the manufacturing and actuation of complex articulated mechanisms at the millimeter scale involves significant challenges, particularly for integration and assembly. Here, we present the third generation of a complex optoelectromechanical device capable of precisely steering a fiber-delivered surgical laser along two axes of motion. The electromagnetically-driven end effector has been fully redesigned with an emphasis on manufacturability and enabling future high-volume production. The device is 3.8 mm in diameter (4 mm with housing), 10 mm in length, and features ±15 degrees range of motion in both axes with a bandwidth of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mrow> <mml:mo>&gt;</mml:mo> </mml:mrow> </mml:math> 230 Hz. We anticipate this type of end effector to have applications in tissue ablation and excision in endoscopic procedures throughout the gastrointestinal tract.

Over the past decade, bioacoustics associated with diverse marine life has become the focus of increasing research. While fixed acoustic devices play important roles in characterizing localized soundscapes, animal-worn devices that record audio alongside physiological metrics provide richer portals to understanding cetacean communication and characterizing sounds in their environment. To facilitate scaling the collection of such multimodal datasets for deep learning applications and to encourage rapid prototyping for new recording capabilities, we present an open-source non-invasive bio-logger that can be deployed on marine animals to record high-quality audio synchronized with an extensible suite of behavioral and environmental sensors. The current implementation is tailored to investigating sperm whale communication and biology. It features four suction cups, three high-bandwidth synchronized hydrophones for audio analysis including directionality, GPS logging and transmission, and sensors for pressure, motion, orientation, temperature, and light. Its hardware and software are both open-source, with designs, fabrication details, and code available online. Lab-based experiments characterize and validate performance including shear adhesion forces, withstanding pressures equivalent to 560 m depths, battery life up to 16.8 hours, audio sensitivity of -205 dB re FS/μPa with a 96 dB dynamic range, multi-threaded data acquisition, drone-based deployments, and GPS-based recoveries. Field experiments record sperm whale vocalizations and behaviors spanning 10 deployments, 44 hours of recording, 20 dives, and up to 967 m depths. Altogether, this platform aims to advance the understanding of marine animal biology and communication within the rapidly evolving and intersecting areas of robotics, bioacoustics, and machine learning.

We introduce a system for real-time sperm whale rendezvous at sea using an autonomous uncrewed aerial vehicle. Our system employs model-based reinforcement learning that combines in situ sensor data with an empirical whale dive model to guide navigation decisions. Key challenges include (i) real-time acoustic tracking in the presence of multiple whales, (ii) distributed communication and decision-making for robot deployments, and (iii) on-board signal processing and long-range detection from fish-trackers. We evaluate our system by conducting rendezvous with sperm whales at sea in Dominica, performing hardware experiments on land, and running simulations using whale trajectories interpolated from marine biologists' surface observations.

Autonomous flapping-wing micro-aerial vehicles (FWMAV) have a host of potential applications such as environmental monitoring, artificial pollination, and search and rescue operations. One of the challenges for achieving these applications is the implementation of an onboard sensor suite due to the small size and limited payload capacity of FWMAVs. The current solution for accurate state estimation is the use of offboard motion capture cameras, thus restricting vehicle operation to a special flight arena. In addition, the small payload capacity and highly nonlinear oscillating dynamics of FWMAVs makes state estimation using onboard sensors challenging due to limited compute power and sensor noise. In this paper, we develop a novel hardware-in-the-loop (HWIL) testing pipeline that recreates flight trajectories of the Harvard RoboBee, a 100 mg FWMAV. We apply this testing pipeline to evaluate a potential suite of sensors for robust altitude and attitude estimation by implementing and characterizing a Complimentary Extended Kalman Filter. The HWIL system includes a mechanical noise generator, such that both trajectories and oscillations can be emulated and evaluated. Our onboard sensing package works toward the future goal of enabling fully autonomous control for micro-aerial vehicles.

Marine data collection devices, such as audio recording tags for marine mammals, must robustly adhere to the skin of the animal using noninvasive attachment mechanisms. As such, devices for studying whale behavior and vocalization typically rely on suction cups. However, suction adhesion exhibits limited attachment duration due to the fragile nature of the cup seal on the surface of interest, reducing useful data collection time compared with more invasive methods. This study introduces a novel passive vacuum regeneration system for suction cups, powered by changes in pressure as the whale dives, to extend tag attachment time. The system uses two cylinders with linked pistons. One cylinder, hermetically sealed, drives the system using variations in external pressure during dives, while the other cylinder, linked to one-way valves, acts as a diaphragm pump, allowing fluid transfer from the suction cup to the external medium. Experimental results showed significant vacuum regeneration, achieving up to 881$\%$ for pumping a suction cup filled with air and 48.4$\%$ for one filled with water. A theoretical model identified promising designs that increase pressure regeneration by increasing the cylinder stroke and the offset between pistons. Overall, these findings suggest that the proposed system can significantly extend data collection periods, paving the way for more effective and robust marine data collection.

Programming physical intelligence into mechanisms holds great promise for machines that can accomplish tasks such as navigation of unstructured environments while utilizing a minimal amount of computational resources and electronic components. In this study, we introduce a design approach for physically intelligent underactuated mechanisms capable of autonomously adjusting their motion in response to environmental interactions. Specifically, multistability is harnessed to sequence the motion of different degrees of freedom in a programmed order. A key aspect of this approach is that this order can be passively reprogrammed through mechanical stimuli arising from interactions with the environment. To showcase our approach, we construct a mechanism that passively sorts objects based on their mass and a four-degree-of-freedom robot capable of autonomously moving away from obstacles. Remarkably, these devices operate without relying on traditional computational architectures and utilize only a single linear actuator.

Low-cost satellites need low-cost propulsion systems. The research summarised in this paper has focused on investigating low-cost propulsion system options for small satellites with specific application to the upcoming UoSAT-12 mini satellite mission. The research began by looking at available propulsion system technology. Low-cost spacecraft engineering techniques were then explored to identify specific system cost drivers for further investigation. This led to parallel research efforts aimed at (1) basic research & development into hybrid rockets to characterise their applicability to low-cost spacecraft, and (2) applied research into low-cost spacecraft systems engineering - to design and implement a system for UoSAT-12. The experimental results from a 400-Newton thrust hydrogen peroxide and polyethylene hybrid motor are presented. Initial results indicate that >90% combustion efficiency is achievable and an experimental hybrid mission could feasibly be developed over the next few years. Additional research into low-cost propulsion is also discussed including the application of a low thrust (20-Newton) bi-propellant rocket engine - the LEROS-20, developed by British Aerospace, Royal Ordnance Rocket Motors Division. The combination of innovative manufacturing techniques along with low-cost procurement practices makes this engine an attractive, low-cost option. Finally, research into decreasing the cost of support subsystems has lead to a simple, low-cost design which is being implemented on UoSAT-12 at a fraction of the cost of that predicted by industry standard models.

Wildlife field operations demand efficient parallel deployment methods to identify and interact with specific individuals, enabling simultaneous collective behavioral analysis, and health and safety interventions. Previous robotics solutions approach the problem from the herd perspective, or are manually operated and limited in scale. We propose a decentralized vision-based multi-quadrotor system for wildlife monitoring that is scalable, low-bandwidth, and sensor-minimal (single onboard RGB camera). Our approach enables robust identification and tracking of large species in their natural habitat. We develop novel vision-based coordination and tracking algorithms designed for dynamic, unstructured environments without reliance on centralized communication or control. We validate our system through real-world experiments, demonstrating reliable deployment in diverse field conditions.

Deploying animal-borne suction-based tag devices on whales has been one of the primary tools used by researchers over the past several decades to gather high-resolution scientific information, such as bioacoustics, heart rate, dive depth, and body orientation. However, the process of successfully applying animal-borne tags is logistically challenging and requires substantial operator skill. Current methods apply tags by approaching the whale in a boat and adhering the tag via a long extension pole. In this study, we explore an alternative approach to apply animal-borne suction-based tag devices using First Person View (FPV) racing drones. These drones have been specifically adapted to withstand exposure to seawater, allowing them to operate effectively in marine environments. The drones are equipped with a custom interface, allowing to release the tag when it is applied on the whale's back. In this study, we present the development of the delivery drone as well as tag deployment techniques. The proposed method was demonstrated on sperm whales (Physeter macrocephalus) off Dominica, resulting in fast deployment time (one minute and fifteen seconds on average) and a relatively high deployment success rate (over 55 %). In addition, the presented deployment process offers a less invasive technique for tagging, as boats are not needed for close approaches. These methods also serve as a framework to enable future development of more automated solutions to apply the tag on exact anatomical targets with controlled initial adhesion pressure and without manual operation.

Dielectric elastomer actuators (DEAs) are soft, electrically-driven artificial muscles with high energy density and high bandwidth. As work requirements increase, the actuator volume must also increase. Integrating sufficiently large DEAs within mechanical linkages for robotic applications can be challenging since the actuators can be of comparable size to the mechanism itself (as with human forearm muscles and hands). Here, we demonstrate a way to use DEAs to power cable-driven mechanisms, thus allowing the actuator to be separated from the mechanism, enabling modularity in design. We detail the manufacture and characterization of scaled-up rolled DEAs for increased work output via a sequential roll-on-roll method, and cable integration for remote actuation. This cable-DEA architecture is used to actuate a pinching gripper, a multi-degree-of-freedom mechanism, and a soft end-effector. This work illustrates a promising method to pair the unique actuation characteristics of DEAs to rigid-material mechanisms.

California blackworms constitute a recently identified animal system exhibiting unusual collective behaviors, in which dozens to thousands of worms entangle to form a “blob” capable of actions like locomotion as an aggregate. In this paper we describe a system of pneumatic soft robots inspired by the blackworms, intended for the study of collective behaviors enabled and mediated by such physical entanglement. Both the robots and worms have high aspect ratio (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\gtrsim 1: 50$</tex>), intertwine in complex 3D configurations, operate both in air and underwater, and can locomote both individually and as a collective. We demonstrate and characterize locomotion for both individual robots and entangled blobs, explore the tunability of entanglement strength, and compare these to the analogous versions in living worms. The robots provide a testbed for studying mechanisms underlying behaviors observed in worm blobs, as well as serving as a platform for studies of novel collective behaviors based on physical entanglement.

Searching for extraterrestrial life and supporting human life in space are traditionally regarded as separate challenges. However, there are significant benefits to an approach that treats them as different aspects of the same essential inquiry: How can we conceptualize life beyond our home planet?

Searching for extraterrestrial life and supporting human life in space are traditionally regarded as separate challenges. However, there are significant benefits to an approach that treats them as different aspects of the same essential problem: How can we conceptualize life beyond our home planet?

Rolling contact joints are an advantageous building block for soft-rigid hybrid robots due to their out-of-plane compliance, low resistance to bending, and wide range of motion. Typically, proprioception in these cable-driven mechanisms is achieved through torque and position sensors at the servomotor actuator. However, this indirect measurement of joint position can be inaccurate when the system is non-ideal (e.g., the cables are extensible, friction is not negligible, or the linkage encounters an external disturbance). Here, we introduce a magnetic sensor integrated into rolling contact joints to measure joint position and force. We then explore the design space of this magnetic sensor by varying the orientation of the magnets and the stiffness of the magnetoelastomer. A multilayer perceptron is used to relate the joint position and force to the magnetometer readings, providing the flexibility to use this sensor with various joint geometries and sensing modalities. We find that the accuracy of this sensing and modeling approach is coupled with the configuration of the magnetic elements, and that our system can predict the joint angle, twist, and contact forces with errors as low as 1.6%, 0.1%, and 8.8%, respectively. This work describes a method for enabling proprioception in rolling contact joints, and, more broadly, compliant joints for rigid-soft hybrid robots.

For flying insects, the transition from flight to surface locomotion requires effective touchdown maneuvers that allow stable landings on a variety of surfaces. Landing behaviors of insects are diverse, with some using more controlled flight approaches to landing, whereas others dampen collision impacts with parts of their bodies. The landing approaches of real insects inspired our current work, where we present a combined mechanical and control approach to achieving safe and accurate landings for flapping-wing microaerial vehicles. For the mechanical approach to landing, we took inspiration from the legs of the crane fly, designing lossy compliant legs that maximize energy dissipation during surface collisions. We explored three features in the compliant leg design: leg stance, number of joints, and joint placement. For the control approach to landing, the challenge lies in overcoming the aerodynamic ground effect near the surface. Leveraging the compliant leg design during impact, we designed the preimpact behavior, drawing inspiration from insect landing trajectories, to increase landing success. The proposed controlled landing sequence includes an initial acceleration from hovering, followed by deceleration toward the target, ending with a nonzero impact velocity, similar to what is observed in insects. Last, using an insect-scale flapping-wing aerial microrobot platform (Harvard RoboBee), we verified the controlled, safe, and accurate landing on natural terrain.

Although legged robots have demonstrated effective mobility in some natural settings, as robot size decreases, obstacles in their environment become challenging to overcome. Small arthropods scale obstacles many times their size through jumps powered by mechanisms that overcome speed and power limitations of muscle alone. The motivation for this study was to explore the marriage of impulsive (jumping) and nonimpulsive (cyclic legged ambulation) behaviors in a centimeter-scale robot. Here, jumping is achieved by striking the ground with a bioinspired appendage connected to a parallel linkage. As the linkage configuration passes through the singularity, a torque reversal occurs whereby elastic energy slowly stored by force-dense velocity-limited shape memory alloy actuators is rapidly released. A passively driven elastic hinge is introduced in the striking arm to mediate ground contact forces and direct jumping. High-speed video recording of the 14-millisecond launch phase reveals previously undocumented takeoff dynamics closely resembling those of springtails. A dynamic model was derived, and an experimentally validated simulation was used to optimize the design of key components. The 2.2-gram, 6.1-centimeter-long mechanism achieved a maximum horizontal jumping distance of 1.4 meters (23 body lengths), surpassing that of similarly sized insects. The mechanism was integrated with an agile quadrupedal microrobot with leg articulation suitable to achieve the ideal jumping posture. The platform demonstrated repeatable directional takeoffs and upright landings, enabling complex maneuvers to overcome obstacles and gaps. Last, we used this bioinspired robot to offer reflection on hypotheses related to springtail jumping behavior.

We aim to improve the adhesion capabilities of electroadhesive pads on rough surfaces by using geometry-driven compliance to increase effective contact area. We present a kirigami-based approach for enhancing compliance through an exploration of geometric features cut into an adhesive disk. We experimentally test a range of geometries, comparing shear adhesion strength to understand structure–function relationships in our chosen parameter space. Our findings indicate that introducing cuts to form serpentine paths in a disk results in longer effective lengths and enhanced compliance, thus requiring less energy to deform into a rough surface. Leveraging this insight and associated scaling analysis, we conclude that serpentine-like features arranged in a radially symmetric wedge configuration achieve high levels of adhesion, even on rough surfaces, enabling robust adhesion relative to featureless electroadhesive disks.

Abstract Mechanical counterpressure (MCP) space suits could offer advantages over current gas-pressurized suits in safety, mobility, and decreased suit complexity and volume. However, a passive MCP space suit design poses challenges with donning and doffing as it must be exceedingly tight, requiring 29.6 kPa of MCP. Equipping the suit with wearable active devices, such as an expanding cuff, is a potential solution to this issue. These devices could allow the suit to loosen and tighten to aid in donning and doffing and to conform to changes in body geometry during movement. Dielectric elastomer actuators (DEAs) are a promising candidate for the active device element of an MCP space suit design due to their compliance, high energy density, long lifetime, and high bandwidth. The high voltage required to drive DEAs can be reduced by subdividing the dielectric layer of the DEA to create DEA multilayers (DEAMs). This work presents a DEAM-based MCP space suit cuff, a fundamental component of a full suit concept, that applies passive pressure through prestretch and loosens upon actuation for donning, doffing, and during movement. The cuff is fabricated using a batch-spray and stamp technique, and it consists of 24 active layers, each 200 µ m in thickness, giving the cuff a total thickness of 6 mm including inactive encapsulation layers. The final cuff design achieves an MCP of 19.52 kPa, a maximum pressure relief of 5.42 kPa, and a response time of 0.7 s. The proposed design can achieve a counterpressure of 29 kPa with a prestretch factor of 2.42. These results demonstrate the capabilities of DEAM-based wearable devices, introducing novel actuation functionality to wearable technology.

Many aquatic organisms utilize suction-based organs to adhere to diverse substrates in unpredictable environments. For multiple fish species, these adhesive discs include a softer disc margin consisting of surface structures called papillae, which stabilize and seal on variable substrates. The size, arrangement, and density of these papillae are quite diverse among different species, generating complex disc patterns produced by these structures. Considering papillae arrangements in three fish species, the Northern Clingfish (Gobiesox maeandricus), Tidepool Snailfish (Liparis florae), and Chilean Clingfish (Sicyases sanguineus), we fabricated physical disc models that tested relevant surface pattern parameters under shear loading conditions. Parameters of interest included the area of papillae-like structures, the spacing between adjacent structures (channel spacing), and the percent coverage of elements relative to the total disc area. To create our models, a soft silicone elastomer was added to a stiff circular suction cup, which was then "stamped" using a laser-etched and thermoformed mold base to create the desired surface patterning. Discs were tested using a robotic arm equipped with a force sensor, which sheared them across smooth and rough surfaces at a fixed speed and distance. The arm was also used to vary the initial compression to test performance under both suction-dominant and friction-dominant preloads. For our designs, patterns with smaller papillae-like structures and channel spacing often produced higher peak forces than those with larger features. However, the design that withstood the highest shear load featured an intermediate pad size and channel spacing, potentially highlighting a balance between overall surface area and fluid channeling. Additionally, discs with surface patterns often outperformed the control discs (no pattern) on both smooth and rough surfaces, but performance was highly dependent on preload, with patterned discs exhibiting benefits with the higher "friction-dominant" preloads.

We introduce a Wireless Signal based Efficient multi-Robot eXploration (WiSER-X) algorithm applicable to a decentralized team of robots exploring an unknown environment with communication bandwidth constraints. WiSER-X relies only on local inter-robot relative position estimates, that can be obtained by exchanging signal pings from onboard sensors such as WiFi, Ultra-Wide Band, amongst others, to inform the exploration decisions of individual robots to minimize redundant coverage overlaps. Furthermore, WiSER-X also enables asynchronous termination without requiring a shared map between the robots. It also adapts to heterogeneous robot behaviors and even complete failures in unknown environment while ensuring complete coverage. Simulations show that WiSER-X leads to 58% lower overlap than a zero-information-sharing baseline algorithm-1 and only 23% more overlap than a full-information-sharing algorithm baseline algorithm-2. Hardware experiments further validate the feasibility of WiSER-X using full onboard sensing.

Optimizing mechanical adhesion to specific human tissue types is a field of research that has gained increasing attention over the past two decades due to its utility for diagnostics, therapeutics, and surgical device design. This is especially relevent for medical devices, which could benefit from the presence of attachment mechanisms in order to better target-specific regions of the gastrointestinal (GI) tract or other soft tissues for sensing, sample collection, and drug release. In this work, and inspired by the tissue anchoring adaptations found in diverse parasitic taxa, we present a design and manufacturing platform for the production of a nonintuitive bioinspired millimeter-scale articulated attachment mechanism using laminate fabrication techniques. The functional design closely mimics the geometry and motions of curved hooks employed by some species of tapeworms to attach to their host's intestinal walls. Here, we show the feasibility of such a mechanism both in terms of attachment capabilities and manufacturability. Successful attachment of a prototype to tissue-simulating synthetic medical hydrogels is demonstrated with an adhesion force limited only by the ultimate strength of the tissue. These results demonstrate the efficacy of parasite-inspired deployable designs as an alternative to, or complement to, existing tissue attachment mechanisms. We also describe the design and manufacturing process workflow and provide insights for scaling the design for mass-production.

While previous studies have explored electroadhesive climbing using the insect-scale Harvard Ambulatory Microrobot platform, the robot's ability to climb reliably over irregular terrain has remained limited. To evaluate potential solutions, we conducted an investigation of the electroadhesive pad design space and characterized the shear force climbing capabilities of the robot with different pad designs. We find that on smooth, flat terrains, a large simple circular footpad structure exhibited the greatest shear forces. However, on rougher inclined surfaces, pads which adjusted the width, length, and number of spoke-like features provide greater compliance and achieve more consistent shear adhesion forces. Such compliant spoke pad designs on rough surfaces performed with 84 % stick reliability and 1.02 kPa average adhesion forces compared to 45 % stick reliability and 0.81 kPa average adhesion forces for a comparable circular pad. We demonstrate the improved climbing capability of the 4.5 cm robot on terrain with 75 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula>m roughness and observe an average increase in climbing speed of 48 % over a range of angles from 0–45 degrees.

Autonomous flapping-wing micro-aerial vehicles (FWMAV) have a host of potential applications such as environmental monitoring, artificial pollination, and search and rescue operations. One of the challenges for achieving these applications is the implementation of an onboard sensor suite due to the small size and limited payload capacity of FWMAVs. The current solution for accurate state estimation is the use of offboard motion capture cameras, thus restricting vehicle operation to a special flight arena. In addition, the small payload capacity and highly non-linear oscillating dynamics of FWMAVs makes state estimation using onboard sensors challenging due to limited compute power and sensor noise. In this paper, we develop a novel hardware-in-the-loop (HWIL) testing pipeline that recreates flight trajectories of the Harvard RoboBee, a 100mg FWMAV. We apply this testing pipeline to evaluate a potential suite of sensors for robust altitude and attitude estimation by implementing and characterizing a Complimentary Extended Kalman Filter. The HWIL system includes a mechanical noise generator, such that both trajectories and oscillatinos can be emulated and evaluated. Our onboard sensing package works towards the future goal of enabling fully autonomous control for micro-aerial vehicles.

Abstract Networks of conductive nanoparticles have been used as electrodes for dielectric elastomer actuator multilayers because of their excellent extensibility and low added stiffness. Nanoparticle network topography, however, has typically effected a tradeoff between conductivity and breakdown strength. This has limited actuators to a corresponding tradeoff between either high operating frequencies and efficiencies or high stresses, strains, and energy densities. This tradeoff is resolved by spatially patterning multiple nanoparticles to produce hybrid electrodes. Sparse networks of high‐aspect‐ratio carbon nanotubes allow for self‐clearing in the body of the electrode, yielding 54.7 V µm −1 breakdown strength, 86.4% that of the neat elastomer. Dense networks of low‐aspect‐ratio carbon black at the external interfaces, meanwhile, provide low contact resistance (44.09 kΩmm). Two tools essential for their practical deployment are developed: a scalable fabrication process and an automated pre‐clearing algorithm. The fabrication method leverages the batch spray and stamp paradigm in concert with vacuum filtration to scalably deposit nanoparticle electrodes with minimal parameter tuning, enabling the production of a 100‐layer actuator capable of 14% strain. The adaptive pre‐clearing algorithm discriminates between and responds to a range of defect‐induced failures in newly fabricated actuators, eliminating the need for human oversight and standardizing the break‐in procedure.

Rendezvous with sperm whales for biological observations is made challenging by their prolonged dive patterns. Here, we propose an algorithmic framework that codevelops multiagent reinforcement learning-based routing (autonomy module) and synthetic aperture radar-based very high frequency (VHF) signal-based bearing estimation (sensing module) for maximizing rendezvous opportunities of autonomous robots with sperm whales. The sensing module is compatible with low-energy VHF tags commonly used for tracking wildlife. The autonomy module leverages in situ noisy bearing measurements of whale vocalizations, VHF tags, and whale dive behaviors to enable time-critical rendezvous of a robot team with multiple whales in simulation. We conducted experiments at sea in the native habitat of sperm whales using an "engineered whale"-a speedboat equipped with a VHF-emitting tag, emulating five distinct whale tracks, with different whale motions. The sensing module shows a median bearing error of 10.55° to the tag. Using bearing measurements to the engineered whale from an acoustic sensor and our sensing module, our autonomy module gives an aggregate rendezvous success rate of 81.31% for a 500-meter rendezvous distance using three robots in postprocessing. A second class of fielded experiments that used acoustic-only bearing measurements to three untagged sperm whales showed an aggregate rendezvous success rate of 68.68% for a 1000-meter rendezvous distance using two robots in postprocessing. We further validated these algorithms with several ablation studies using a sperm whale visual encounter dataset collected by marine biologists.

Programming physical intelligence into mechanisms holds great promise for machines that can accomplish tasks such as navigation of unstructured environments while utilizing a minimal amount of computational resources and electronic components. In this study, we introduce a novel design approach for physically intelligent under-actuated mechanisms capable of autonomously adjusting their motion in response to environmental interactions. Specifically, multistability is harnessed to sequence the motion of different degrees of freedom in a programmed order. A key aspect of this approach is that these sequences can be passively reprogrammed through mechanical stimuli that arise from interactions with the environment. To showcase our approach, we construct a four degree of freedom robot capable of autonomously navigating mazes and moving away from obstacles. Remarkably, this robot operates without relying on traditional computational architectures and utilizes only a single linear actuator.

To navigate complex terrains, insects use diverse tarsal structures (adhesive pads, claws, spines) to reliably attach to and locomote across substrates. This includes surfaces of variable roughness and inclination, which often require reliable transitions from ambulatory to scansorial locomotion. Using bioinspired physical models as a means for comparative research, our study specifically focused on the diversity of tarsal spines, which facilitate locomotion via frictional engagement and shear force generation. For spine designs, we took inspiration from ground beetles (family: Carabidae), which is a largely terrestrial group known for their quick locomotion. Evaluating four different species, we found that the hind legs host linear rows of rigid spines along the entire tarsus. By taking morphometric measurements of the spines, we highlighted parameters of interest (e.g., spine angle and aspect ratio) in order to test their relationship to shear forces sustained during terrain interactions. We systematically evaluated these parameters using spines cut from stainless steel shim attached to a small acrylic sled loaded with various weights. The sled was placed on 3D-printed models of rough terrain, randomly generated using fractal Brownian motion, while a motorized pulley system applied force to the spines. A force sensor measured the reaction force on the terrain, recording shear force before failure occurred. Initial shear tests highlighted the importance of spine angle, with bioinspired anisotropic designs producing higher shear forces. Using these data, we placed the best (50° angle) and worst (90° angle) performing spines on the legs of our insect-scale ambulatory robot physical model. We then tested the robot on various surfaces at 0°, 10°, and 20° inclines, seeing similar success with the more bioinspired spines.

A fabrication methodology for piezoelectric motors based on multiple unimorph arms at the mesoscale is proposed. The combination of laser micromachining and lamination steps allows for a stator with a diameter of 9 mm and a thickness of 0.267 mm to be batch manufactured. This design is investigated via a finite element analysis where it is shown that the contact condition between the stator unimorph arms and rotor is dependent on the input drive frequency. The fabricated stator is then characterized experimentally where it is shown that a shift in the sinusoidal drive frequency from 3220 Hz to 3900 Hz results in a change to the rotational direction of the rotor from the positive to the negative direction. The torque of the motor is evaluated numerically to demonstrate the performance of the mesoscale piezoelectric motor in both rotational directions.

We present 4k video and whole transcriptome data for seven deep-sea invertebrate animals collected in the Eastern Pacific Ocean during a research expedition onboard the Schmidt Ocean Institute's R/V Falkor in August of 2021. The animals include one jellyfish (Atolla sp.), three siphonophores (Apolemia sp., Praya sp., and Halistemma sp.), one larvacean (Bathochordaeus mcnutti), one tunicate (Pyrosomatidae sp.), and one ctenophore (Lampocteis sp.). Four of the animals were sequenced with long-read RNA sequencing technology, such that the reads themselves define a reference assembly for those animals. The larvacean tissues were successfully preserved in situ and has paired long-read reference data and short read quantitative transcriptomic data for within-specimen analyses of gene expression. Additionally, for three animals we provide quantitative image data, and a 3D model for one siphonophore. The paired image and transcriptomic data can be used for species identification, species description, and reference genetic data for these deep-sea animals.

Aquatic organisms utilizing attachment often contend with unpredictable environments that can dislodge them from substrates. To counter these forces, many organisms (e.g. fish, cephalopods) have evolved suction-based organs for adhesion. Morphology is diverse, with some disc shapes deviating from a circle to more ovate designs. Inspired by the diversity of multiple aquatic species, we investigated how bioinspired cups with different disc shapes performed in shear loading conditions. These experiments highlighted pertinent physical characteristics found in biological discs (regions of stiffness, flattened margins, a sealing rim), as well as ecologically relevant shearing conditions. Disc shapes of fabricated cups included a standard circle, ellipses, and other bioinspired designs. To consider the effects of sealing, these stiff silicone cups were produced with and without a soft rim. Cups were tested using a force-sensing robotic arm, which directionally sheared them across surfaces of varying roughness and compliance in wet conditions while measuring force. In multiple surface and shearing conditions, elliptical and teardrop shapes outperformed the circle, which suggests that disc shape and distribution of stiffness may play an important role in resisting shear. Additionally, incorporating a soft rim increased cup performance on rougher substrates, highlighting interactions between the cup materials and surfaces asperities. To better understand how these cup designs may resist shear, we also utilized a visualization technique (frustrated total internal reflection; FTIR) to quantify how contact area evolves as the cup is sheared.

Abstract The rising number of devices created using pop‐up microelectromechanical systems (MEMS) and related folding‐based assembly techniques highlights the need for robust design and manufacturing workflows to support the wide range of device variations. To push the bounds of miniaturization, design for manufacturing is key in dealing with fabrication challenges. Iterative building of intermediate device prototypes is a promising way to explore an often very large design space and can highlight mechanical limitations that may not be obvious to the designer. Manufacturing of pop‐up MEMS devices is, however, typically a lengthy process with lamination taking a significant percentage of the build time, compared to layer machining and component assembly. To expedite the design process, researchers often prototype multiple iterations at larger scales prior to committing to at‐scale designs. In this study, an at‐scale rapid prototyping workflow for pop‐up MEMS devices is introduced. This study also includes flexure design considerations for castellated hinges, to approach the behavior of an ideal pin joint. The new proposed workflow uses more accessible lower‐cost equipment and materials and reduces lamination time by over 95% (10 min lamination vs a 3.5 h lamination) compared to the previous heated press process, which is validated through a series of prototypes.

Tracking and following objects of interest is critical to several robotics use cases, ranging from industrial automation to logistics and warehousing, to healthcare and security. In this paper, we present a robotic system to detect, track, and follow any object in real-time. Our approach, dubbed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">follow anything</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FAn</i> ), is an open-vocabulary and multimodal model — it is not restricted to concepts seen at training time and can be applied to novel classes at inference time using text, images, or click queries. Leveraging rich visual descriptors from large-scale pre-trained models ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">foundation models</i> ), <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FAn</i> can detect and segment objects by matching multimodal queries (text, images, clicks) against an input image sequence. These detected and segmented objects are tracked across image frames, all while accounting for occlusion and object re-emergence. We demonstrate <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FAn</i> on a real-world robotic system (a micro aerial vehicle), and report its ability to seamlessly follow the objects of interest in a real-time control loop. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">FAn</i> can be deployed on a laptop with a lightweight (6-8 GB) graphics card, achieving a throughput of 6-20 frames per second. To enable rapid adoption, deployment, and extensibility, we opensource our code on our project webpage. We also encourage the reader to watch our 5-minute explainer video.

Revolutionary advancements in underwater imaging, robotics, and genomic sequencing have reshaped marine exploration. We present and demonstrate an interdisciplinary approach that uses emerging quantitative imaging technologies, an innovative robotic encapsulation system with in situ RNA preservation and next-generation genomic sequencing to gain comprehensive biological, biophysical, and genomic data from deep-sea organisms. The synthesis of these data provides rich morphological and genetic information for species description, surpassing traditional passive observation methods and preserved specimens, particularly for gelatinous zooplankton. Our approach enhances our ability to study delicate mid-water animals, improving research in the world's oceans.