In a time of upheaval, robotics has an opportunity to offer long-term solutions and radical change.

Elasticity has been linked to the remarkable propulsive efficiency of pulse-jet animals such as the squid and jellyfish, but reports that quantify the underlying dynamics or demonstrate its application in robotic systems are rare. This work identifies the pulse-jet propulsion mode used by these animals as a coupled mass-spring-mass oscillator, enabling the design of a flexible self-propelled robot

A squid-like robot leverages resonance to match the swimming efficiency of biological animals.

The predatory strike of dragonfly larvae can inspire the design of fast robotic movement with enhanced control and precision.

The biomechanics underlying the predatory strike of dragonfly larvae is not yet understood. Dragonfly larvae are aquatic ambush predators, capturing their prey with a strongly modified extensible mouthpart. The current theory of hydraulic pressure being the driving force of the predatory strike can be refuted by our manipulation experiments and reinterpretation of former studies. Here, we report evidence

Miniaturized robotic laser steering opens new horizons for laser microsurgery.

A swarm of agile fish-robots uses vision-based implicit coordination to demonstrate self-organizing behaviors in a laboratory tank.

Sampling genetic material from phytoplankton in open ocean eddies becomes more precise and efficient using a heterogeneous network of autonomous marine robots.

The creation of multiarticulated mechanisms for use with minimally invasive surgical tools is difficult because of fabrication, assembly, and actuation challenges on the millimeter scale of these devices. Nevertheless, such mechanisms are desirable for granting surgeons greater precision and dexterity to manipulate and visualize tissue at the surgical site. Here, we describe the construction of a complex

Many fish species gather by the thousands and swim in harmony with seemingly no effort. Large schools display a range of impressive collective behaviors, from simple shoaling to collective migration and from basic predator evasion to dynamic maneuvers such as bait balls and flash expansion. A wealth of experimental and theoretical work has shown that these complex three-dimensional (3D) behaviors can

The deep chlorophyll maximum (DCM) layer is an ecologically important feature of the open ocean. The DCM cannot be observed using aerial or satellite remote sensing; thus, in situ observations are essential. Further, understanding the responses of microbes to the environmental processes driving their metabolism and interactions requires observing in a reference frame that moves with a plankton population

Soft materials and machine learning combine to enable a sensor that distinguishes bending, stretching, and compression.

Multimodal tactile sensors help robot hands accurately identify grasped objects by measuring thermal properties in addition to contact loads.

Soft sensors have been playing a crucial role in detecting different types of physical stimuli to part or the entire body of a robot, analogous to mechanoreceptors or proprioceptors in biology. Most of the currently available soft sensors with compact form factors can detect only a single deformation mode at a time due to the limitation in combining multiple sensing mechanisms in a limited space. However

Robot hands with tactile perception can improve the safety of object manipulation and also improve the accuracy of object identification. Here, we report the integration of quadruple tactile sensors onto a robot hand to enable precise object recognition through grasping. Our quadruple tactile sensor consists of a skin-inspired multilayer microstructure. It works as thermoreceptor with the ability to

Biological grippers can inspire the development of a new class of versatile soft grippers in agrorobotics and beyond.

Composite hydrogel robots can achieve programmable locomotion using light and magnetic fields.

Advances in neuroscience are inspiring developments in robotics and vice versa.

Achieving versatile robot locomotion requires motor skills that can adapt to previously unseen situations. We propose a multi-expert learning architecture (MELA) that learns to generate adaptive skills from a group of representative expert skills. During training, MELA is first initialized by a distinct set of pretrained experts, each in a separate deep neural network (DNN). Then, by learning the combination

Swarm robotics will tackle real-world applications by leveraging automatic design, heterogeneity, and hierarchical self-organization.

The design of soft matter in which internal fuels or an external energy input can generate locomotion and shape transformations observed in living organisms is a key challenge. Such materials could assist in productive functions that may range from robotics to smart management of chemical reactions and communication with cells. In this context, hydrated matter that can function in aqueous media would

Localization algorithms applied to acoustic tags for tracking marine animals can also be used to localize marine robots.

An autonomous underwater vehicle, named Clio, can sample ocean basin–scale biogeochemistry at depths up to 6000 meters.

Knowing the displacement capacity and mobility patterns of industrially exploited (i.e., fished) marine resources is key to establishing effective conservation management strategies in human-impacted marine ecosystems. Acquiring accurate behavioral information of deep-sea fished ecosystems is necessary to establish the sizes of marine protected areas within the framework of large international societal

Vast and diverse microbial communities exist within the ocean. To better understand the global influence of these microorganisms on Earth’s climate, we developed a robot capable of sampling dissolved and particulate seawater biochemistry across ocean basins while still capturing the fine-scale biogeochemical processes therein. Carbon and other nutrients are acquired and released by marine microorganisms

Human-human social constructs drive human-robot interactions; robotics is thus intertwined with issues surrounding inequity and racial injustices.

A minimalist robot construction strategy offers versatility and compatibility in actuating diverse objects on demand.

Robots for picking in e-commerce warehouses require rapid computing of efficient and smooth robot arm motions between varying configurations. Recent results integrate grasp analysis with arm motion planning to compute optimal smooth arm motions; however, computation times on the order of tens of seconds dominate motion times. Recent advances in deep learning allow neural networks to quickly compute

Millirobots that can adapt to unstructured environments, operate in confined spaces, and interact with a diverse range of objects would be desirable for exploration and biomedical applications. The continued development of millirobots, however, requires simple and scalable fabrication techniques. Here, we propose a minimalist approach to construct millirobots by coating inanimate objects with a composited

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

Speed is essential in wildlife surveys due to the dynamic movement of animals throughout their environment and potentially extreme changes in weather. In this work, we present a multirobot path-planning method for conducting aerial surveys over large areas designed to make the best use of limited flight time. Unlike current survey path-planning solutions based on geometric patterns or integer programs

A multidrone path-planning algorithm enables drones to scout Adélie penguin colonies in Antarctica.

A winged drone demonstrates aggressive and agile flight by morphing its wings and tail.

Deep reinforcement learning enables quadruped robots to traverse challenging natural environments using only proprioception.

Legged locomotion can extend the operational domain of robots to some of the most challenging environments on Earth. However, conventional controllers for legged locomotion are based on elaborate state machines that explicitly trigger the execution of motion primitives and reflexes. These designs have increased in complexity but fallen short of the generality and robustness of animal locomotion. Here

A hybrid analog-digital computing platform using memristors enables faster, more energy-efficient, and adaptive real-time robot control.

Algorithms for mobile robotic systems are generally implemented on purely digital computing platforms. Developing alternative computational platforms may lead to more energy-efficient and responsive mobile robotics. Here, we report a hybrid analog-digital computing platform enabled by memristors on a mobile inverted pendulum robot. Our mobile robotic system can tune the conductance states of memristors

It is generally accepted among biology and engineering communities that insects are unstable at hover. However, existing approaches that rely on direct averaging do not fully capture the dynamical features and stability characteristics of insect flight. Here, we reveal a passive stabilization mechanism that insects exploit through their natural wing oscillations: vibrational stabilization. This stabilization

Elucidating the neural and psychological mechanisms underlying people’s interpretation of robot behavior can inform the design of interactive autonomous systems, such as social robots and automated vehicles.

Studies of insect flight reveal how flapping-induced vibrations augment flight stability of tailless flapping-wing flyers.

The increasing presence of robots in society necessitates a deeper understanding into what attitudes people have toward robots. People may treat robots as mechanistic artifacts or may consider them to be intentional agents. This might result in explaining robots’ behavior as stemming from operations of the mind (intentional interpretation) or as a result of mechanistic design (mechanistic interpretation)

Replacing the human hand with artificial devices of equal capability and effectiveness is a long-standing challenge. Even the most advanced hand prostheses, which have several active degrees of freedom controlled by the electrical signals of the stump’s residual muscles, do not achieve the complexity, dexterity, and adaptability of the human hand. Thus, prosthesis abandonment rate remains high due

Continued advances in machine learning could enable robots to solve tasks on a human level and adapt to changing conditions.

Co-creation leads the way for bioinspired prosthetics with improved design and performance.

The game of curling can be considered a good test bed for studying the interaction between artificial intelligence systems and the real world. In curling, the environmental characteristics change at every moment, and every throw has an impact on the outcome of the match. Furthermore, there is no time for relearning during a curling match due to the timing rules of the game. Here, we report a curling

Little Eyes by Samanta Schweblin offers a thought experiment in human-robot interaction.

A cable-driven robot that tracks flying insects at close range offers a useful method to study insects in free flight.

Tensegrity structures provide both structural integrity and flexibility through the combination of stiff struts and a network of flexible tendons. These structures exhibit useful properties: high stiffness-to-mass ratio, controllability, reliability, structural flexibility, and large deployment. The integration of smart materials into tensegrity structures would provide additional functionality and

3D-printed flexible tensegrities with metamaterial properties enable customizable complex locomotion in soft robots.

The creation of autonomous subgram microrobots capable of complex behaviors remains a grand challenge in robotics largely due to the lack of microactuators with high work densities and capable of using power sources with specific energies comparable to that of animal fat (38 megajoules per kilogram). Presently, the vast majority of microrobots are driven by electrically powered actuators; consequently

Batteries with conformal shape and multiple functionalities could provide new degrees of freedom in the design of robotic devices. For example, the ability to provide both load bearing and energy storage can increase the payload and extend the operational range for robots. However, realizing these kinds of structural power devices requires the development of materials with suitable mechanical and ion

Multifunctional Zn-air batteries provide energy storage and a body-integrated protective cover for robots.

Continued development of untethered insect-scale robots will require codesigned power and actuation strategies.

Powered prostheses aim to mimic the missing biological limb with controllers that are finely tuned to replicate the nominal gait pattern of non-amputee individuals. Unfortunately, this control approach poses a problem with real-world ambulation, which includes tasks such as crossing over obstacles, where the prosthesis trajectory must be modified to provide adequate foot clearance and ensure timely

The aerobatic maneuvers of swifts could be very useful for micro aerial vehicle missions. Rapid arrests and turns would allow flight in cluttered and unstructured spaces. However, these decelerating aerobatic maneuvers have been difficult to demonstrate in flapping wing craft to date because of limited thrust and control authority. Here, we report a 26-gram X-wing ornithopter of 200-millimeter fuselage

The identification and solution of a major efficiency loss in small flapping wing drones lead to more agile aerobatic maneuvers.

Robots have a role in addressing the secondary impacts of infectious disease outbreaks by helping us sustain social distancing, monitoring and improving mental health, supporting education, and aiding in economic recovery.

Spiders use adhesive, stretchable, and translucent webs to capture their prey. However, sustaining the capturing capability of these webs can be challenging because the webs inevitably invite contamination, thus reducing its adhesion force. To overcome these challenges, spiders have developed strategies of using webs to sense prey and clean contaminants. Here, we emulate the capturing strategies of

Vision serves as an essential sensory input for insects but consumes substantial energy resources. The cost to support sensitive photoreceptors has led many insects to develop high visual acuity in only small retinal regions and evolve to move their visual systems independent of their bodies through head motion. By understanding the trade-offs made by insect vision systems in nature, we can design

An insect-scale visual sensing system indicates the return of active vision for robotics.