Journal: Science Robotics

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AAAS

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ISSN

2470-9476

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2017 - 2019182020 - 202539
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Publications1 - 10 of 57
  • Exploration of underwater life with an acoustically controlled soft robotic fish
    Item type: Journal Article
    Katzschmann, Robert K.; DelPreto, Joseph; MacCurdy, Robert; et al. (2018)
    Science Robotics
    Closeup exploration of underwater life requires new forms of interaction, using biomimetic creatures that are capable of agile swimming maneuvers, equipped with cameras, and supported by remote human operation. Current robotic prototypes do not provide adequate platforms for studying marine life in their natural habitats. This work presents the design, fabrication, control, and oceanic testing of a soft robotic fish that can swim in three dimensions to continuously record the aquatic life it is following or engaging. Using a miniaturized acoustic communication module, a diver can direct the fish by sending commands such as speed, turning angle, and dynamic vertical diving. This work builds on previous generations of robotic fish that were restricted to one plane in shallow water and lacked remote control. Experimental results gathered from tests along coral reefs in the Pacific Ocean show that the robotic fish can successfully navigate around aquatic life at depths ranging from 0 to 18 meters. Furthermore, our robotic fish exhibits a lifelike undulating tail motion enabled by a soft robotic actuator design that can potentially facilitate a more natural integration into the ocean environment. We believe that our study advances beyond what is currently achievable using traditional thruster-based and tethered autonomous underwater vehicles, demonstrating methods that can be used in the future for studying the interactions of aquatic life and ocean dynamics.
  • Robotic surfaces with reversible, spatiotemporal control for shape morphing and object manipulation
    Item type: Journal Article
    Liu, Ke; Hacker, Felix; Daraio, Chiara (2021)
    Science Robotics
    Continuous and controlled shape morphing is essential for soft machines to conform, grasp, and move while interacting safely with their surroundings. Shape morphing can be achieved with two-dimensional (2D) sheets that reconfigure into target 3D geometries, for example, using stimuli-responsive materials. However, most existing solutions lack the ability to reprogram their shape, face limitations on attainable geometries, or have insufficient mechanical stiffness to manipulate objects. Here, we develop a soft, robotic surface that allows for large, reprogrammable, and pliable shape morphing into smooth 3D geometries. The robotic surface consists of a layered design composed of two active networks serving as artificial muscles, one passive network serving as a skeleton, and cover scales serving as an artificial skin. The active network consists of a grid of strips made of heat-responsive liquid crystal elastomers (LCEs) containing stretchable heating coils. The magnitude and speed of contraction of the LCEs can be controlled by varying the input electric currents. The 1D contraction of the LCE strips activates in-plane and out-of-plane deformations; these deformations are both necessary to transform a flat surface into arbitrary 3D geometries. We characterize the fundamental deformation response of the layers and derive a control scheme for actuation. We demonstrate that the robotic surface provides sufficient mechanical stiffness and stability to manipulate other objects. This approach has potential to address the needs of a range of applications beyond shape changes, such as human-robot interactions and reconfigurable electronics.
  • Accelerating the pace of innovation in robotics by fostering diversity and inclusive leadership
    Item type: Review Article
    Macari, Daniela; Fratzl, Alex; Keplinger, Ksenia; et al. (2024)
    Science Robotics
    Diverse and inclusive teams are not merely a moral imperative but also a catalyst for scientific excellence in robotics. Drawing from literature, a comprehensive citation analysis, and expert interviews, we derive seven main benefits of diversity and inclusion and propose a leadership guide for roboticists to reap these benefits.
  • Soft robotic patient-specific hydrodynamic model of aortic stenosis and ventricular remodeling
    Item type: Journal Article
    Rosalia, Luca; Ozturk, Caglar; Goswami, Debkalpa; et al. (2023)
    Science Robotics
    Aortic stenosis (AS) affects about 1.5 million people in the United States and is associated with a 5-year survival rate of 20% if untreated. In these patients, aortic valve replacement is performed to restore adequate hemodynamics and alleviate symptoms. The development of next-generation prosthetic aortic valves seeks to provide enhanced hemodynamic performance, durability, and long-term safety, emphasizing the need for high-fidelity testing platforms for these devices. We propose a soft robotic model that recapitulates patient-specific hemodynamics of AS and secondary ventricular remodeling which we validated against clinical data. The model leverages 3D-printed replicas of each patient's cardiac anatomy and patient-specific soft robotic sleeves to recreate the patients' hemodynamics. An aortic sleeve allows mimicry of AS lesions due to degenerative or congenital disease, whereas a left ventricular sleeve recapitulates loss of ventricular compliance and diastolic dysfunction (DD) associated with AS. Through a combination of echocardiographic and catheterization techniques, this system is shown to recreate clinical metrics of AS with greater controllability compared with methods based on image-guided aortic root reconstruction and parameters of cardiac function that rigid systems fail to mimic physiologically. Last, we leverage this model to evaluate the hemodynamic benefit of transcatheter aortic valves in a subset of patients with diverse anatomies, etiologies, and disease states. Through the development of a high-fidelity model of AS and DD, this work demonstrates the use of soft robotics to recreate cardiovascular disease, with potential applications in device development, procedural planning, and outcome prediction in industrial and clinical settings.
  • Biomimetic temperature-sensing layer for artificial skins
    Item type: Journal Article
    Di Giacomo, Raffaele; Bonanomi, Luca; Costanza, Vincenzo; et al. (2017)
    Science Robotics
  • A professional slackliner robot
    Item type: Other Journal Item
    Mintchev, Stefano (2021)
    Science Robotics
  • ANYmal parkour: Learning agile navigation for quadrupedal robots
    Item type: Journal Article
    Hoeller, David; Rudin, Nikita; Sako, Dhionis; et al. (2024)
    Science Robotics
    Performing agile navigation with four-legged robots is a challenging task because of the highly dynamic motions, contacts with various parts of the robot, and the limited field of view of the perception sensors. Here, we propose a fully learned approach to training such robots and conquer scenarios that are reminiscent of parkour challenges. The method involves training advanced locomotion skills for several types of obstacles, such as walking, jumping, climbing, and crouching, and then using a high-level policy to select and control those skills across the terrain. Thanks to our hierarchical formulation, the navigation policy is aware of the capabilities of each skill, and it will adapt its behavior depending on the scenario at hand. In addition, a perception module was trained to reconstruct obstacles from highly occluded and noisy sensory data and endows the pipeline with scene understanding. Compared with previous attempts, our method can plan a path for challenging scenarios without expert demonstration, offline computation, a priori knowledge of the environment, or taking contacts explicitly into account. Although these modules were trained from simulated data only, our real-world experiments demonstrate successful transfer on hardware, where the robot navigated and crossed consecutive challenging obstacles with speeds of up to 2 meters per second.
  • Bioinspired wing and tail morphing extends drone flight capabilities
    Item type: Journal Article
    Ajanic, Enrico; Feroskhan, Mir; Mintchev, Stefano; et al. (2020)
    Science Robotics
    The aerodynamic designs of winged drones are optimized for specific flight regimes. Large lifting surfaces provide maneuverability and agility but result in larger power consumption, and thus lower range, when flying fast compared with small lifting surfaces. Birds like the northern goshawk meet these opposing aerodynamic requirements of aggressive flight in dense forests and fast cruising in the open terrain by adapting wing and tail areas. Here, we show that this morphing strategy and the synergy of the two morphing surfaces can notably improve the agility, maneuverability, stability, flight speed range, and required power of a drone in different flight regimes by means of an avian-inspired drone. We characterize the drone’s flight capabilities for different morphing configurations in wind tunnel tests, optimization studies, and outdoor flight tests. These results shed light on the avian use of wings and tails and offer an alternative design principle for drones with adaptive flight capabilities.
  • A closed-loop hand prosthesis with simultaneous intraneural tactile and position feedback
    Item type: Journal Article
    D’Anna, Edoardo; Valle, Giacomo; Mazzoni, Alberto; et al. (2019)
    Science Robotics
  • Drone-assisted collection of environmental DNA from tree branches for biodiversity monitoring
    Item type: Journal Article
    Aucone, Emanuele; Kirchgeorg, Steffen; Valentini, Alice; et al. (2023)
    Science Robotics
    The protection and restoration of the biosphere is crucial for human resilience and well-being, but the scarcity of data on the status and distribution of biodiversity puts these efforts at risk. DNA released into the environment by organisms, i.e., environmental DNA (eDNA), can be used to monitor biodiversity in a scalable manner if equipped with the appropriate tool. However, the collection of eDNA in terrestrial environments remains a challenge because of the many potential surfaces and sources that need to be surveyed and their limited accessibility. Here, we propose to survey biodiversity by sampling eDNA on the outer branches of tree canopies with an aerial robot. The drone combines a force-sensing cage with a haptic-based control strategy to establish and maintain contact with the upper surface of the branches. Surface eDNA is then collected using an adhesive surface integrated in the cage of the drone. We show that the drone can autonomously land on a variety of branches with stiffnesses between 1 and 103 newton/meter without prior knowledge of their structural stiffness and with robustness to linear and angular misalignments. Validation in the natural environment demonstrates that our method is successful in detecting animal species, including arthropods and vertebrates. Combining robotics with eDNA sampling from a variety of unreachable aboveground substrates can offer a solution for broad-scale monitoring of biodiversity.
Publications1 - 10 of 57