Bioinspired dual-stiffness origami

Origami manufacturing has led to considerable advances in the field of foldable structures with innovative applications in robotics, aerospace, and metamaterials. However, existing origami are either load-bearing structures that are prone to tear and fail if overloaded or resilient soft structures with limited load capability. In this manuscript, we describe an origami structure that displays both high load bearing and high resilience characteristics. The structure, which is inspired by insect wings, consists of a prestretched elastomeric membrane, akin to the soft resilin joints of insect wings, sandwiched between rigid tiles, akin to the rigid cuticles of insect wings. The dual-stiffness properties of the proposed structure are validated by using the origami as an element of a quadcopter frame that can withstand aerodynamic forces within its flight envelope but softens during collisions to avoid permanent damage. In addition, we demonstrate an origami gripper that can be used for rigid grasping but softens to avoid overloading of the manipulated objects.

Source: Sciencemag.org – Science Robotics Latest Content

A highly sensitive, self-powered triboelectric auditory sensor for social robotics and hearing aids

The auditory system is the most efficient and straightforward communication strategy for connecting human beings and robots. Here, we designed a self-powered triboelectric auditory sensor (TAS) for constructing an electronic auditory system and an architecture for an external hearing aid in intelligent robotic applications. Based on newly developed triboelectric nanogenerator (TENG) technology, the TAS showed ultrahigh sensitivity (110 millivolts/decibel). A TAS with the broadband response from 100 to 5000 hertz was achieved by designing the annular or sectorial inner boundary architecture with systematic optimization. When incorporated with intelligent robotic devices, TAS demonstrated high-quality music recording and accurate voice recognition for realizing intelligent human-robot interaction. Furthermore, the tunable resonant frequency of TAS was achieved by adjusting the geometric design of inner boundary architecture, which could be used to amplify a specific sound wave naturally. On the basis of this unique property, we propose a hearing aid with the TENG technique, which can simplify the signal processing circuit and reduce the power consuming. This work expresses notable advantages of using TENG technology to build a new generation of auditory systems for meeting the challenges in social robotics.

Source: Sciencemag.org – Science Robotics Latest Content

Optimized flocking of autonomous drones in confined environments

We address a fundamental issue of collective motion of aerial robots: how to ensure that large flocks of autonomous drones seamlessly navigate in confined spaces. The numerous existing flocking models are rarely tested on actual hardware because they typically neglect some crucial aspects of multirobot systems. Constrained motion and communication capabilities, delays, perturbations, or the presence of barriers should be modeled and treated explicitly because they have large effects on collective behavior during the cooperation of real agents. Handling these issues properly results in additional model complexity and a natural increase in the number of tunable parameters, which calls for appropriate optimization methods to be coupled tightly to model development. In this paper, we propose such a flocking model for real drones incorporating an evolutionary optimization framework with carefully chosen order parameters and fitness functions. We numerically demonstrated that the induced swarm behavior remained stable under realistic conditions for large flock sizes and notably for large velocities. We showed that coherent and realistic collective motion patterns persisted even around perturbing obstacles. Furthermore, we validated our model on real hardware, carrying out field experiments with a self-organized swarm of 30 drones. This is the largest of such aerial outdoor systems without central control reported to date exhibiting flocking with collective collision and object avoidance. The results confirmed the adequacy of our approach. Successfully controlling dozens of quadcopters will enable substantially more efficient task management in various contexts involving drones.

Source: Sciencemag.org – Science Robotics Latest Content

Autonomous task sequencing in a robot swarm

Robot swarms mimic natural systems in which collective abilities emerge from the interaction of individuals. So far, the swarm robotics literature has focused on the emergence of mechanical abilities (e.g., push a heavy object) and simple cognitive abilities (e.g., select a path between two alternatives). In this article, we present a robot swarm in which a complex cognitive ability emerged. This swarm was able to collectively sequence tasks whose order of execution was a priori unknown. Because sequencing tasks is an albeit simple form of planning, the robot swarm that we present provides a different perspective on a pivotal debate in the history of artificial intelligence: the debate on planning in robotics. In the proposed swarm, the two robotics paradigms—deliberative (sense-model-plan-act) and reactive (sense-act)—that are traditionally considered antithetical coexist in a particular way: The ability to plan emerges at the collective level from the interaction of reactive individuals.

Source: Sciencemag.org – Science Robotics Latest Content

Rotary-actuated folding polyhedrons for midwater investigation of delicate marine organisms

Self-folding polyhedra have emerged as a viable design strategy for a wide range of applications, with advances largely made through modeling and experimentation at the micro- and millimeter scale. Translating these concepts to larger scales for practical purposes is an obvious next step; however, the size, weight, and method of actuation present a new set of problems to overcome. We have developed large-scale folding polyhedra to rapidly and noninvasively enclose marine organisms in the water column. The design is based on an axisymmetric dodecahedron net that is folded by an external assembly linkage. Requiring only a single rotary actuator to fold, the device is suited for remote operation onboard underwater vehicles and has been field-tested to encapsulate a variety of delicate deep-sea organisms. Our work validates the use of self-folding polyhedra for marine biological applications that require minimal actuation to achieve complex motion. The device was tested to 700 m, but the system was designed to withstand full ocean depth (11 km) pressures. We envision broader terrestrial applications of rotary-actuated folding polyhedra, ranging from large-scale deployable habitats and satellite solar arrays to small-scale functional origami microelectromechanical systems.

Source: Sciencemag.org – Science Robotics Latest Content

Personalized machine learning for robot perception of affect and engagement in autism therapy

Robots have the potential to facilitate future therapies for children on the autism spectrum. However, existing robots are limited in their ability to automatically perceive and respond to human affect, which is necessary for establishing and maintaining engaging interactions. Their inference challenge is made even harder by the fact that many individuals with autism have atypical and unusually diverse styles of expressing their affective-cognitive states. To tackle the heterogeneity in children with autism, we used the latest advances in deep learning to formulate a personalized machine learning (ML) framework for automatic perception of the children’s affective states and engagement during robot-assisted autism therapy. Instead of using the traditional one-size-fits-all ML approach, we personalized our framework to each child using their contextual information (demographics and behavioral assessment scores) and individual characteristics. We evaluated this framework on a multimodal (audio, video, and autonomic physiology) data set of 35 children (ages 3 to 13) with autism, from two cultures (Asia and Europe), and achieved an average agreement (intraclass correlation) of ~60% with human experts in the estimation of affect and engagement, also outperforming nonpersonalized ML solutions. These results demonstrate the feasibility of robot perception of affect and engagement in children with autism and have implications for the design of future autism therapies.

Source: Sciencemag.org – Science Robotics Latest Content

Development of a magnetic microrobot for carrying and delivering targeted cells

The precise delivery of targeted cells through magnetic field–driven microrobots/carriers is a promising technique for targeted therapy and tissue regeneration. This paper presents a microrobot designed with a burr-like porous spherical structure for carrying and delivering targeted cells in vivo under a magnetic gradient field–driven mechanism. The robot was fabricated by using three-dimensional laser lithography and coated with Ni for magnetic actuation and Ti for biocompatibility. Numerical and experimental studies demonstrated that the proposed microrobot design could enhance magnetic driving capability, promote cell-carrying capacity, and benefit cell viability. Microrobots loaded with cells could be automatically controlled to reach a desired site by using a self-constructed electromagnetic coil system, as verified by in vivo transport of cell-cultured microrobots in zebrafish embryos. The carried cells could be spontaneously released from the microrobot to the surrounding tissues; in vitro experiments showed that cells from the microrobot were directly released onto the desired site or were able to pass through the blood vessel–like microchannel to arrive at the delivery area. Further in vivo cell-releasing tests were performed on nude mice, followed by histological study. This research provides a microrobotic device platform for regenerative medicine and cell-based therapy.

Source: Sciencemag.org – Science Robotics Latest Content

Prosthesis with neuromorphic multilayered e-dermis perceives touch and pain

The human body is a template for many state-of-the-art prosthetic devices and sensors. Perceptions of touch and pain are fundamental components of our daily lives that convey valuable information about our environment while also providing an element of protection from damage to our bodies. Advances in prosthesis designs and control mechanisms can aid an amputee’s ability to regain lost function but often lack meaningful tactile feedback or perception. Through transcutaneous electrical nerve stimulation (TENS) with an amputee, we discovered and quantified stimulation parameters to elicit innocuous (nonpainful) and noxious (painful) tactile perceptions in the phantom hand. Electroencephalography (EEG) activity in somatosensory regions confirms phantom hand activation during stimulation. We invented a multilayered electronic dermis (e-dermis) with properties based on the behavior of mechanoreceptors and nociceptors to provide neuromorphic tactile information to an amputee. Our biologically inspired e-dermis enables a prosthesis and its user to perceive a continuous spectrum from innocuous to noxious touch through a neuromorphic interface that produces receptor-like spiking neural activity. In a pain detection task (PDT), we show the ability of the prosthesis and amputee to differentiate nonpainful or painful tactile stimuli using sensory feedback and a pain reflex feedback control system. In this work, an amputee can use perceptions of touch and pain to discriminate object curvature, including sharpness. This work demonstrates possibilities for creating a more natural sensation spanning a range of tactile stimuli for prosthetic hands.

Source: Sciencemag.org – Science Robotics Latest Content