The importance of swarm robotics systems in both academic research and real-world applications is steadily increasing. However, to reach widespread adoption, new models that ensure the secure cooperation of large groups of robots need to be developed. This work introduces a method to encapsulate cooperative robotic missions in an authenticated data structure known as a Merkle tree. With this method

In both science and science fiction, robot swarms are out of control.

To effectively perform collective monitoring of dynamic environments, a robot swarm needs to adapt to changes by processing the latest information and discarding outdated beliefs. We show that in a swarm composed of robots relying on local sensing, adaptation is better achieved if the robots have a shorter rather than longer communication range. This result is in contrast with the widespread belief

Swarms of ground-based robots are presently limited to relatively simple environments, which we attribute in part to the lack of locomotor capabilities needed to traverse complex terrain. To advance the field of terradynamically capable swarming robotics, inspired by the capabilities of multilegged organisms, we hypothesize that legged robots consisting of reversibly chainable modular units with appropriate

A swarm of simple active particles confined in a flexible scaffold is a promising system to make mobile and deformable superstructures. These soft structures can perform tasks that are difficult to carry out for monolithic robots because they can infiltrate narrow spaces, smaller than their size, and move around obstacles. To achieve such tasks, the origin of the forces the superstructures develop

Quadrotors are among the most agile flying robots. However, planning time-optimal trajectories at the actuation limit through multiple waypoints remains an open problem. This is crucial for applications such as inspection, delivery, search and rescue, and drone racing. Early works used polynomial trajectory formulations, which do not exploit the full actuator potential because of their inherent smoothness

Excavators are widely used for material handling applications in unstructured environments, including mining and construction. Operating excavators in a real-world environment can be challenging due to extreme conditions—such as rock sliding, ground collapse, or excessive dust—and can result in fatalities and injuries. Here, we present an autonomous excavator system (AES) for material loading tasks

Analysis of Caenorhabditis elegans natural movement and optogenetic control of its muscle cells enable controlled locomotion.

Learning from the locomotion of natural organisms is one of the most effective strategies for designing microrobots. However, the development of bioinspired microrobots is still challenging because of technical bottlenecks such as design and seamless integration of high-performance actuation mechanism and high-density energy source for untethered locomotion. Directly harnessing the activation energy

Agility and trajectory control are two desirable features for robotics, but they become very challenging for soft robots without rigid structures to support rapid manipulations. Here, a curved piezoelectric thin film driven at its structural resonant frequency is used as the main body of an insect-scale soft robot for its fast translational movements, and two electrostatic footpads are used for its

Robots are at the frontier of space and deep-sea exploration; they will continue to lead our search into the unknown.

Autonomous drones will play an essential role in human-machine teaming in future search and rescue (SAR) missions. We present a prototype that finds people fully autonomously in densely occluded forests. In the course of 17 field experiments conducted over various forest types and under different flying conditions, our drone found, in total, 38 of 42 hidden persons. For experiments with predefined

Visual terrain-relative navigation (VTRN) is a localization method based on registering a source image taken from a robotic vehicle against a georeferenced target image. With high-resolution imagery databases of Earth and other planets now available, VTRN offers accurate, drift-free navigation for air and space robots even in the absence of external positioning signals. Despite its potential for high

Signal processing of thermal images that are autonomously collected by a drone detects people in densely occluded forests.

Science fiction missed the large role that robots are playing at Fukushima Daiichi.

Mesobot, an autonomous underwater vehicle, addresses specific unmet needs for observing and sampling a variety of phenomena in the ocean’s midwaters. The midwater hosts a vast biomass, has a role in regulating climate, and may soon be exploited commercially, yet our scientific understanding of it is incomplete. Mesobot has the ability to survey and track slow-moving animals and to correlate the animals’

Robotic navigation on land, through air, and in water is well researched; numerous robots have successfully demonstrated motion in these environments. However, one frontier for robotic locomotion remains largely unexplored—below ground. Subterranean navigation is simply hard to do, in part because the interaction forces of underground motion are higher than in air or water by orders of magnitude and

A bioinspired soft robot burrows through shallow dry sand with remarkable speed and maneuverability.

Tracking deep ocean animals over their daily cycles will revolutionize our understanding of the largest biome on Earth.

Tactile feedback is a natural pathway to robot dexterity in unstructured settings.

Perceiving and handling deformable objects is an integral part of everyday life for humans. Automating tasks such as food handling, garment sorting, or assistive dressing requires open problems of modeling, perceiving, planning, and control to be solved. Recent advances in data-driven approaches, together with classical control and planning, can provide viable solutions to these open challenges. In

The ability to reliably grasp and manipulate novel objects is a grand challenge for robotics.

Science fiction was prescient about many aspects of grasping and manipulation, but can it keep up with new advances?

The ever-changing nature of human environments presents great challenges to robot manipulation. Objects that robots must manipulate vary in shape, weight, and configuration. Important properties of the robot, such as surface friction and motor torque constants, also vary over time. Before robot manipulators can work gracefully in homes and businesses, they must be adaptive to such variations. This

The process of modeling a series of hand-object parameters is crucial for precise and controllable robotic in-hand manipulation because it enables the mapping from the hand’s actuation input to the object’s motion to be obtained. Without assuming that most of these model parameters are known a priori or can be easily estimated by sensors, we focus on equipping robots with the ability to actively self-identify

Humans have long been fascinated by the opportunities afforded through augmentation. This vision not only depends on technological innovations but also critically relies on our brain’s ability to learn, adapt, and interface with augmentation devices. Here, we investigated whether successful motor augmentation with an extra robotic thumb can be achieved and what its implications are on the neural representation

The world outside our laboratories seldom conforms to the assumptions of our models. This is especially true for dynamics models used in control and motion planning for complex high–degree of freedom systems like deformable objects. We must develop better models, but we must also consider that, no matter how powerful our simulators or how big our datasets, our models will sometimes be wrong. What is

Policy gradient methods can be used for mechanical and computational co-design of robot manipulators.

Humans use all surfaces of the hand for contact-rich manipulation. Robot hands, in contrast, typically use only the fingertips, which can limit dexterity. In this work, we leveraged a potential energy–based whole-hand manipulation model, which does not depend on contact wrench modeling like traditional approaches, to design a robotic manipulator. Inspired by robotic caging grasps and the high levels

The ability to grab, hold, and manipulate objects is a vital and fundamental operation in biological and engineering systems. Here, we present a soft gripper using a simple material system that enables precise and rapid grasping, and can be miniaturized, modularized, and remotely actuated. This soft gripper is based on kirigami shells—thin, elastic shells patterned with an array of cuts. The kirigami

Scifi assumes creating a robot mother will be easy, research indicates otherwise, but both suggest you might not want one anyway.

Small-scale soft-bodied machines that respond to externally applied magnetic field have attracted wide research interest because of their unique capabilities and promising potential in a variety of fields, especially for biomedical applications. When the size of such machines approach the sub-millimeter scale, their designs and functionalities are severely constrained by the available fabrication methods

Advances in materials science will blur the boundaries between robots and the materials from which they are composed.

A watchmaker’s approach yields small, agile, soft machines.

Powering miniature robots using actuating materials that mimic skeletal muscle is attractive because conventional mechanical drive systems cannot be readily downsized. However, muscle is not the only mechanically active system in nature, and the thousandfold contraction of eukaryotic DNA into the cell nucleus suggests an alternative mechanism for high-stroke artificial muscles. Our analysis reveals

Super-contractile artificial muscle that is inspired by DNA generates more work than skeletal muscle.

The establishment of a new academic field is often characterized by a phase of rapid growth, as seen over the last decade in the field of soft robotics. However, such growth can be followed by an equally rapid decline if concerted efforts are not made by the community. Here, we argue that for soft robotics to take root and have impact in the next decade, we must move beyond “soft for soft’s sake” and

Falling leaves flutter from side to side due to passive and intrinsic fluid-body coupling. Exploiting the dynamics of passive fluttering could lead to fresh perspectives for the locomotion and manipulation of thin, planar objects in fluid environments. Here, we show that the time-varying density distribution within a thin, planar body effectively elicits minimal momentum control to reorient the principal

Compliant, biomimetic actuation technologies that are both efficient and powerful are necessary for robotic systems that may one day interact, augment, and potentially integrate with humans. To this end, we introduce a fluid-driven muscle-like actuator fabricated from inexpensive polymer tubes. The actuation results from a specific processing of the tubes. First, the tubes are drawn, which enhances

Bioinspired hybrid soft robots that combine living and synthetic components are an emerging field in the development of advanced actuators and other robotic platforms (i.e., swimmers, crawlers, and walkers). The integration of biological components offers unique characteristics that artificial materials cannot precisely replicate, such as adaptability and response to external stimuli. Here, we present

Active hydrogels with dynamic wettability move spontaneously on the surface of water like a common water strider.

Although there have been notable advances in adhesive materials, the ability to program attaching and detaching behavior in these materials remains a challenge. Here, we report a borate ester polymer hydrogel that can rapidly switch between adhesive and nonadhesive states in response to a mild electrical stimulus (voltages between 3.0 and 4.5 V). This behavior is achieved by controlling the exposure

Mussel-inspired electro-responsive adhesive hydrogels enable robot climbing on conductive surfaces.

Hydrogels are an exciting class of materials for new and emerging robotics. For example, actuators based on hydrogels have impressive deformability and responsiveness. Studies into hydrogels with autonomous locomotive abilities, however, are limited. Existing hydrogels achieve locomotion through the application of cyclical stimuli or chemical modifications. Here, we report the fabrication of active

Composite membrane origami has been an efficient and effective method for constructing transformable mechanisms while considerably simplifying their design, fabrication, and assembly; however, its limited load-bearing capability has restricted its application potential. With respect to wheel design, membrane origami offers unique benefits compared with its conventional counterparts, such as simple

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

Mimicking biological neuromuscular systems’ sensory motion requires the unification of sensing and actuation in a singular artificial muscle material, which must not only actuate but also sense their own motions. These functionalities would be of great value for soft robotics that seek to achieve multifunctionality and local sensing capabilities approaching natural organisms. Here, we report a soft

Tunable, soft, and multifunctional robots are contributing to developments in medical and rehabilitative robotics, human-machine interaction, and intelligent home technology. A key aspect of soft robot fabrication is the ability to use flexible and efficient schemes to enable the seamless and simultaneous integration of configurable structures. Here, we report a strategy for programming design features

The world was unprepared for the COVID-19 pandemic, and recovery is likely to be a long process. Robots have long been heralded to take on dangerous, dull, and dirty jobs, often in environments that are unsuitable for humans. Could robots be used to fight future pandemics? We review the fundamental requirements for robotics for infectious disease management and outline how robotic technologies can

Robot swarms have, to date, been constructed from artificial materials. Motile biological constructs have been created from muscle cells grown on precisely shaped scaffolds. However, the exploitation of emergent self-organization and functional plasticity into a self-directed living machine has remained a major challenge. We report here a method for generation of in vitro biological robots from frog

Science fiction cannot match the admirable inventiveness of Perseverance, Ingenuity, and other planetary rovers.

Perseverance could be the first robot to find Mars microfossils.

This special issue showcases developments in microactuation, microparticle control, and micro/nanorobots for biomedicine.

Future developments in micromanufacturing will require advances in micromanipulation tools. Several robotic micromanipulation methods have been developed to position micro-objects mostly in air and in liquids. The air-water interface is a third medium where objects can be manipulated, offering a good compromise between the two previously mentioned ones. Objects at the interface are not subjected to

Neutrophil-based microrobots accomplish the mission of crossing the blood-brain barrier for targeted drug delivery.

Reinforcement learning enables microswimmers to navigate through noisy and unexplored real-world environments.

Artificial microswimmers that can replicate the complex behavior of active matter are often designed to mimic the self-propulsion of microscopic living organisms. However, compared with their living counterparts, artificial microswimmers have a limited ability to adapt to environmental signals or to retain a physical memory to yield optimized emergent behavior. Different from macroscopic living systems

Swimming biohybrid microsized robots (e.g., bacteria- or sperm-driven microrobots) with self-propelling and navigating capabilities have become an exciting field of research, thanks to their controllable locomotion in hard-to-reach areas of the body for noninvasive drug delivery and treatment. However, current cell-based microrobots are susceptible to immune attack and clearance upon entering the body

Microscale programmable shape-memory actuators based on reversible electrochemical reactions can provide exciting opportunities for microrobotics.