The grand challenges of Science Robotics

Developing Biohybrid Robotic Jellyfish (Aurelia aurita) for Free-swimming Tests in the Laboratory and in the Field

Biohybrid robotics is a growing field that incorporates both live tissues and engineered materials to build robots that address current limitations in robots, including high power consumption and low damage tolerance. One approach is to use microelectronics to enhance whole organisms, which has previously been achieved to control the locomotion of insects. However, the robotic control of jellyfish swimming offers additional advantages, with the potential to become a new ocean monitoring tool in conjunction with existing technologies. Here, we delineate protocols to build a self-contained swim controller using commercially available microelectronics, embed the device into live jellyfish, and calculate vertical swimming speeds in both laboratory conditions and coastal waters. Using these methods, we previously demonstrated enhanced swimming speeds up to threefold, compared to natural jellyfish swimming, in laboratory and in situ experiments. These results offered insights into both designing low-power robots and probing the structure-function of basal organisms. Future iterations of these biohybrid robotic jellyfish could be used for practical applications in ocean monitoring.

Bringing Together Robotics, Neuroscience, and Psychology: Lessons Learned From an Interdisciplinary Project

The diversified methodology and expertise of interdisciplinary research teams provide the opportunity to overcome the limited perspectives of individual disciplines. This is particularly true at the interface of Robotics, Neuroscience, and Psychology as the three fields have quite different perspectives and approaches to offer. Nonetheless, aligning backgrounds and interdisciplinary expectations can present challenges due to varied research cultures and practices. Overcoming these challenges stands at the beginning of each productive collaboration and thus is a mandatory step in cognitive neurorobotics. In this article, we share eight lessons that we learned from our ongoing interdisciplinary project on human-robot and robot-robot interaction in social settings. These lessons provide practical advice for scientists initiating interdisciplinary research endeavors. Our advice can help to avoid early problems and deal with differences between research fields, prepare for and anticipate challenges, align project expectations, and speed up research progress, thus promoting effective interdisciplinary research across Robotics, Neuroscience, and Psychology.

Independent Pattern Formation of Nanorod and Nanoparticle Swarms under an Oscillating Field

Natural swarms can be formed by various creatures. The swarms can conduct demanded behaviors to adapt to their living environments, such as passing through harsh terrains and protecting each other from predators. At micrometer and nanometer scales, formation of a swarm pattern relies on the physical or chemical interactions between the agents owing to the absence of an on-board device. Independent pattern formation of different swarms, especially under the same input, is a more challenging task. In this work, a swarm of nickel nanorods is proposed and by exploiting its different behavior with the nanoparticle swarm, independent pattern formation of diverse microrobotic swarms under the same environment can be conducted. A mathematical model for the nanorod swarm is constructed, and the mechanism is illustrated. Two-region pattern changing of the nanorod swarm is discovered and compared with the one-region property of the nanoparticle swarm. Experimental characterization of the nanorod swarm pattern is conducted to prove the concept and validate the effectiveness of the theoretical analysis. Furthermore, independent pattern formation of different microrobotic swarms was demonstrated. The pattern of the nanorod swarm could be adjusted while the other swarm was kept unchanged. Simultaneous pattern changing of two swarms was achieved as well. As a fundamental research on the microrobotic swarm, this work presents how the nanoscale magnetic anisotropy of building agents affects their macroscopic swarm behaviors and promotes further development on the independent control of microrobotic swarms under a global field input.

Preliminary clinical experience of robot-assisted surgery in treatment with genioplasty

Genioplasty is the main way to treat diseases such as chin asymmetry, dysplasia and overdevelopment, which involve the three-dimensional direction abnormalities of the chin. Since this kind of surgery mainly uses intraoral incisions, the narrow surgical field of intraoral incisions and the surrounding important neurovascular tissues make it easy for complications, to occur during the osteotomy process, which results in greater surgical risks. The first craniofacial-plastic surgical robot (CPSR-I) system is developed to complete the precise positioning and improve the surgeon's force perception ability. The Kalman filtering method is adopted to reduce the interference of sensor signal noise. An adaptive fuzzy control system, which has strong robustness and adaptability to the environment, is designed to improve the stability of robot-assisted surgical operations. To solve the problem of the depth perception, we propose an automatic bone drilling control strategy that combines position and force conditions to ensure that the robot can automatically stop when the bone is penetrated. On the basis of model surgery and animal experiments, preliminary experiments were carried out clinically. Based on the early results of 6 patients, the robot-assisted approach appears to be a safe and effective strategy for genioplasty.

Service Robots in the Healthcare Sector

Traditionally, advances in robotic technology have been in the manufacturing industry due to the need for collaborative robots. However, this is not the case in the service sectors, especially in the healthcare sector. The lack of emphasis put on the healthcare sector has led to new opportunities in developing service robots that aid patients with illnesses, cognition challenges and disabilities. Furthermore, the COVID-19 pandemic has acted as a catalyst for the development of service robots in the healthcare sector in an attempt to overcome the difficulties and hardships caused by this virus. The use of service robots are advantageous as they not only prevent the spread of infection, and reduce human error but they also allow front-line staff to reduce direct contact, focusing their attention on higher priority tasks and creating separation from direct exposure to infection. This paper presents a review of various types of robotic technologies and their uses in the healthcare sector. The reviewed technologies are a collaboration between academia and the healthcare industry, demonstrating the research and testing needed in the creation of service robots before they can be deployed in real-world applications and use cases. We focus on how robots can provide benefits to patients, healthcare workers, customers, and organisations during the COVID-19 pandemic. Furthermore, we investigate the emerging focal issues of effective cleaning, logistics of patients and supplies, reduction of human errors, and remote monitoring of patients to increase system capacity, efficiency, resource equality in hospitals, and related healthcare environments.

Sensorless environment stiffness and interaction force estimation for impedance control tuning in robotized interaction tasks

Industrial robots are increasingly used to perform tasks requiring an interaction with the surrounding environment (e.g., assembly tasks). Such environments are usually (partially) unknown to the robot, requiring the implemented controllers to suitably react to the established interaction. Standard controllers require force/torque measurements to close the loop. However, most of the industrial manipulators do not have embedded force/torque sensor(s) and such integration results in additional costs and implementation effort. To extend the use of compliant controllers to sensorless interaction control, a model-based methodology is presented in this paper. Relying on sensorless Cartesian impedance control, two Extended Kalman Filters (EKF) are proposed: an EKF for interaction force estimation and an EKF for environment stiffness estimation. Exploiting such estimations, a control architecture is proposed to implement a sensorless force loop (exploiting the provided estimated force) with adaptive Cartesian impedance control and coupling dynamics compensation (exploiting the provided estimated environment stiffness). The described approach has been validated in both simulations and experiments. A Franka EMIKA panda robot has been used. A probing task involving different materials (i.e., with different - unknown - stiffness properties) has been considered to show the capabilities of the developed EKFs (able to converge with limited errors) and control tuning (preserving stability). Additionally, a polishing-like task and an assembly task have been implemented to show the achieved performance of the proposed methodology.

Monolithic Three-Dimensional Functionally Graded Hydrogels for Bioinspired Soft Robots Fabrication

Bioinspired soft robotics aims at reproducing the complex hierarchy and architecture of biological tissues within artificial systems to achieve the typical motility and adaptability of living organisms. The development of suitable fabrication approaches to produce monolithic bodies provided with embedded variable morphological and mechanical properties, typically encountered in nature, is still a technological challenge. Here we report on a novel manufacturing approach to produce three-dimensional functionally graded hydrogels (3D-FGHs) provided with a controlled porosity gradient conferring them variable stiffness. 3D-FGHs are fabricated by means of a custom-designed liquid foam templating (LFT) technique, which relies on the inclusion of air bubbles generated by a blowing agent into the monomer-based template solution during ultraviolet-induced photopolymerization. The 3D-FGHs' apparent Young's modulus ranges from 0.37 MPa (bulky hydrogel region) to 0.09 MPa (highest porosity region). A fish-shaped soft swimmer is fabricated to demonstrate the feasibility of the LFT technique to produce bioinspired robots. Mobility tests show a significant improvement in terms of swimming speed when the robot is provided with a graded body. The proposed manufacturing approach constitutes an enabling solution for the development of macroscopic functionally graded hydrogel-based structures usable in biomimetic underwater soft robotics applications.

Spider Origami: Folding Principle of Jumping Spider Leg Joints for Bioinspired Fluidic Actuators

Jumping spiders (Phidippus regius) are known for their ability to traverse various terrains and have targeted jumps within the fraction of a second to catch flying preys. Different from humans and insects, spiders use muscles to flex their legs, and hydraulic actuation for extension. By pressurizing their inner body fluid, they can achieve fast leg extensions for running and jumping. Here, the working principle of the articular membrane covering the spider leg joint pit is investigated. This membrane is highly involved in walking, grasping, and jumping motions. Hardness and stiffness of the articular membrane is studied using nanoindentation tests and preparation methods for scanning electron microscopy and histology are developed to give detailed information about the inner and outer structure of the leg joint and its membrane. Inspired by the stroller umbrella-like folding mechanism of the articular membrane, a robust thermoplastic polyurethane-based rotary semifluidic actuator is demonstrated, which shows increased durability, achieves working angles over 120°, produces high torques which allows lifts over 100 times of its own weight and jumping abilities. The developed actuator can be used for future grasping tasks, safe human-robot interactions and multilocomotion ground robot applications, and it can shed light into spider locomotion-related questions.

The ethics of algorithms: key problems and solutions

Research on the ethics of algorithms has grown substantially over the past decade. Alongside the exponential development and application of machine learning algorithms, new ethical problems and solutions relating to their ubiquitous use in society have been proposed. This article builds on a review of the ethics of algorithms published in 2016 (Mittelstadt et al. Big Data Soc 3(2), 2016). The goals are to contribute to the debate on the identification and analysis of the ethical implications of algorithms, to provide an updated analysis of epistemic and normative concerns, and to offer actionable guidance for the governance of the design, development and deployment of algorithms.

In the soft grip of nature

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

A comparative study of state-of-the-art driving strategies for autonomous vehicles

The autonomous vehicle is regarded as a promising technology with the potential to reshape mobility and solve many traffic issues, such as accessibility, efficiency, convenience, and especially safety. Many previous studies on driving strategies mainly focused on the low-level detailed driving behaviors or specific traffic scenarios but lacked the high-level driving strategy studies. Though researchers showed increasing interest in driving strategies, there still has no comprehensive answer on how to proactively implement safe driving. After analyzing several representative driving strategies, we propose three characteristic dimensions that are important to measure driving strategies: preferred objective, risk appetite, and collaborative manner. According to these three characteristic dimensions, we categorize existing driving strategies of autonomous vehicles into four kinds: defensive driving strategies, competitive driving strategies, negotiated driving strategies, and cooperative driving strategies. This paper provides a timely comparative review of these four strategies and highlights the possible directions for improving the high-level driving strategy design.

Millimeter-Scale Soft Continuum Robots for Large-Angle and High-Precision Manipulation by Hybrid Actuation

Developing small-scale soft continuum robots with large-angle steering capacity and high-precision manipulation offers broad opportunities in various biomedical settings. However, existing continuum robots reach the bottleneck in actuation on account of the contradiction among small size, compliance actuation, large tender range, high precision, and small dynamic error. Herein, a 3D-printed millimeter-scale soft continuum robot with an ultrathin hollow skeleton wall (300 μm) and a large inner-to-outer ratio (0.8) is reported. After coating a thin ferromagnetic elastomer layer (≈100-150 μm), the proposed soft continuum robot equipped with hybrid actuation (tendon- and magnetic-driven mode) achieves large-angle (up to 100°) steering and high-precision (low to 2 μm for static positioning) micromanipulation simultaneously. Specifically, the robot implements an ultralow dynamic tracking error of ≈10 μm, which is ≈30-fold improved than the state of art. Combined with a microneedle/knife or nasopharyngeal swab, the robot reveals the potential for versatile biomedical applications, such as drug injection on the target tissue, diseased tissue ablation, and COVID-19 nasopharyngeal sampling. The proposed millimeter-scale soft continuum robot presents remarkable advances in large-range and high-precise actuation, which provides a new method for miniature continuum robot design and finds broad applications in biomedical engineering.

Biomedical Micro-/Nanomotors: From Overcoming Biological Barriers to In Vivo Imaging

Self-propelled micro- and nanomotors (MNMs) have shown great potential for applications in the biomedical field, such as active targeted delivery, detoxification, minimally invasive diagnostics, and nanosurgery, owing to their tiny size, autonomous motion, and navigation capacities. To enter the clinic, biomedical MNMs request the biodegradability of their manufacturing materials, the biocompatibility of chemical fuels or externally physical fields, the capability of overcoming various biological barriers (e.g., biofouling, blood flow, blood-brain barrier, cell membrane), and the in vivo visual positioning for autonomous navigation. Herein, the recent advances of synthetic MNMs in overcoming biological barriers and in vivo motion-tracking imaging techniques are highlighted. The challenges and future research priorities are also addressed. With continued attention and innovation, it is believed that, in the future, biomedical MNMs will pave the way to improve the targeted drug delivery efficiency.

Ultrasound Doppler-guided real-time navigation of a magnetic microswarm for active endovascular delivery

Swarming micro/nanorobots offer great promise in performing targeted delivery inside diverse hard-to-reach environments. However, swarm navigation in dynamic environments challenges delivery capability and real-time swarm localization. Here, we report a strategy to navigate a nanoparticle microswarm in real time under ultrasound Doppler imaging guidance for active endovascular delivery. A magnetic microswarm was formed and navigated near the boundary of vessels, where the reduced drag of blood flow and strong interactions between nanoparticles enable upstream and downstream navigation in flowing blood (mean velocity up to 40.8 mm/s). The microswarm-induced three-dimensional blood flow enables Doppler imaging from multiple viewing configurations and real-time tracking in different environments (i.e., stagnant, flowing blood, and pulsatile flow). We also demonstrate the ultrasound Doppler-guided swarm formation and navigation in the porcine coronary artery ex vivo. Our strategy presents a promising connection between swarm control and real-time imaging of microrobotic swarms for localized delivery in dynamic environments.

Unipolar stroke, electroosmotic pump carbon nanotube yarn muscles

Success in making artificial muscles that are faster and more powerful and that provide larger strokes would expand their applications. Electrochemical carbon nanotube yarn muscles are of special interest because of their relatively high energy conversion efficiencies. However, they are bipolar, meaning that they do not monotonically expand or contract over the available potential range. This limits muscle stroke and work capacity. Here, we describe unipolar stroke carbon nanotube yarn muscles in which muscle stroke changes between extreme potentials are additive and muscle stroke substantially increases with increasing potential scan rate. The normal decrease in stroke with increasing scan rate is overwhelmed by a notable increase in effective ion size. Enhanced muscle strokes, contractile work-per-cycle, contractile power densities, and energy conversion efficiencies are obtained for unipolar muscles.

Squid-inspired robots perform swimmingly

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

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.

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.

Linear and rotational microhydraulic actuators driven by electrowetting

Microhydraulic actuators offer a new way to convert electrical power to mechanical power on a microscale with an unmatched combination of power density and efficiency. Actuators work by combining surface tension force contributions from a large number of droplets distorted by electrowetting electrodes. This paper reports on the behavior of microgram-scale linear and rotational microhydraulic actuators with output force/weight ratios of 5500, cycle frequencies of 4 kilohertz, <1-micrometer movement precision, and accelerations of 3 kilometers/second² The power density and the efficiency of the actuators were characterized by simultaneously measuring the mechanical work performed and the electrical power applied. Maximum output power density was 0.93 kilowatt/kilogram, comparable with the best electric motors. At maximum power, the actuator was 60% efficient, but efficiencies were as high as 83% at lower power. Rotational actuators demonstrated a torque density of 79 newton meters/kilogram, substantially more than electric motors of comparable diameter. Scaling the droplet pitch from 100 to 48 micrometers increased power density from 0.27 to 0.93 kilowatt/kilogram, validating the quadratic scaling of actuator power.

ChemOS: Orchestrating autonomous experimentation

ChemOS aims to catalyze the expansion of autonomous laboratories and to disrupt the conventional approach to experimentation.

Magnetic Array Assisted Triboelectric Nanogenerator Sensor for Real-Time Gesture Interaction

In human-machine interaction, robotic hands are useful in many scenarios. To operate robotic hands via gestures instead of handles will greatly improve the convenience and intuition of human-machine interaction. Here, we present a magnetic array assisted sliding triboelectric sensor for achieving a real-time gesture interaction between a human hand and robotic hand. With a finger's traction movement of flexion or extension, the sensor can induce positive/negative pulse signals. Through counting the pulses in unit time, the degree, speed, and direction of finger motion can be judged in real-time. The magnetic array plays an important role in generating the quantifiable pulses. The designed two parts of magnetic array can transform sliding motion into contact-separation and constrain the sliding pathway, respectively, thus improve the durability, low speed signal amplitude, and stability of the system. This direct quantization approach and optimization of wearable gesture sensor provide a new strategy for achieving a natural, intuitive, and real-time human-robotic interaction.

Wearable triboelectric sensors for biomedical monitoring and human-machine interface

A growing advocacy of healthy and quality life makes wearable electronics spring up. Triboelectric nanogenerator (TENG) has developed as an energy harvesting technology and as an advanced sensor technology in wearable electronics. The triboelectric sensor (TS) is sensitive to the mechanical motion and driven by the motion itself. Therefore, TS is capable of monitoring certain vital signs and kinds of movements of human body. Based on these monitoring, novel human-machine interfaces (HMIs) can be established. In this review, a comprehensive overview of some key progresses in this field over last 5 years are presented. Several main aspects of biomedical monitoring based on TSs are classified: pulse/cardiac/micro-motion, respiration/airflow/vibration, and pressure/tactile/body movement. The major types of HMIs taking these biomedical monitoring as basis are introduced accordingly: eye movement, voice/auditory, gesture/joint movement, and touch/tactile based HMIs. Finally, the current limitations and future trends are put forward for biomedical monitoring and HMIs based on TSs.

Evaluation of the Genetic Association and Expressions of Notch-2 /Jagged-1 in Patients with Type 2 Diabetes Mellitus

Background

Diabetes mellitus (DM) is the world's most common cause of chronic kidney diseases (CKD), with approximately 1 in 4 adults with DM having CKD and 1 out of 10 to 20% of DM patients die from CKD.

Objective

The current study aims to investigate the correlation between Notch-2 and Jag-1expressions and specific inflammation biomarkers IL-1β and IL-6 with different stages of diabetic nephropathy.

Methods

From August 2018 to January 2019, three hundred subjects were recruited for this study. One hundred and fifty subjects were healthy and age-matched to the diabetic group and selected as a control group. Another 150 patients with an established diagnosis of type 2 diabetes (T2DM) according to the criteria of the American Diabetes Association (ADA) were also recruited. Blood specimens were eventually used to identify the expressions Notch-2 and Jagged-1 and the levels of inflammatory biomarkers IL-1β and IL-6.

Result

The current study shows a significant increase in gene expression and inflammatory biomarkers in patients with moderate and severe diabetic nephropathy compared to the control group. However, there was no significant difference between healthy control and mild diabetic nephropathy patients. This study shows a close association between the increase in the levels of inflammatory biomarkers IL-1β and IL-6 as well as the gene expressions levels of both Notch-2 and Jag-1 with human diabetic nephropathy.

Conclusion

According to our findings, we emphasize the use of Notch-2 and Jag-1 expressions and IL-1β and IL-6 levels as potential biomarkers for different stages of diabetic nephropathy.

Kinesin-Recruiting Microtubules Exhibit Collective Gliding Motion while Forming Motor Trails

Microtubules gliding on surfaces coated with kinesin motors are minimalist experimental systems for studying collective behavior. Collective behavior in these systems arises from interactions between filaments, for example, from steric interactions, depletion forces, or cross-links. To maximize the utilization of system components and the production of work, it is desirable to achieve mutualistic interactions leading to the congregations of both types of agents, that is, cytoskeletal filaments and molecular motors. To this end, we used a microtubule-kinesin system, where motors reversibly bind to the surface via an interaction between a hexahistidine (His₆) tag on the motor and a Ni(II)-nitrilotriacetic acid (Ni-NTA) moiety on the surface. The surface density of binding sites for kinesin motors was increased relative to our earlier work, driving the motors from the solution to the surface. Characterization of the motor-surface interactions in the absence of microtubules yielded kinetic parameters consistent with previous data and revealed the capacity of the surface to support two-dimensional motor diffusion. The motor density gradually fell over 2 h, presumably due to the stripping of Ni(II) from the NTA moieties on the surface. Microtubules gliding on these reversibly bound motors were unable to cross each other and at high enough densities began to align and form long, dense bundles. The kinesin motors accumulated in trails surrounding the microtubule bundles and participated in microtubule transport.

Progress in Nanorobotics for Advancing Biomedicine

Nanorobotics, which has long been a fantasy in the realm of science fiction, is now a reality due to the considerable developments in diverse fields including chemistry, materials, physics, information and nanotechnology in the past decades. Not only different prototypes of nanorobots whose sizes are nanoscale are invented for various biomedical applications, but also robotic nanomanipulators which are able to handle nano-objects obtain substantial achievements for applications in biomedicine. The outstanding achievements in nanorobotics have significantly expanded the field of medical robotics and yielded novel insights into the underlying mechanisms guiding life activities, remarkably showing an emerging and promising way for advancing the diagnosis & treatment level in the coming era of personalized precision medicine. In this review, the recent advances in nanorobotics (nanorobots, nanorobotic manipulations) for biomedical applications are summarized from several facets (including molecular machines, nanomotors, DNA nanorobotics, and robotic nanomanipulators), and the future perspectives are also presented.

Protrusion mechanism study in sipunculid worms as model for developing bio-inspired linear actuators

The invertebrates ability to adapt to the environment during motion represents an intriguing feature to inspire robotic systems. We analysed the sipunculid speciesPhascolosoma stephensoni(Sipunculidae, Annelida), and quantitatively studied the motion behaviour of this unsegmented worm. The hydrostatic skeleton and the muscle activity make the infaunalP.stephensoniable to extrude part of its body (the introvert) from its burrow to explore the environment by remaining hidden within the rocky substrate where it settled. The introvert protrusion is associated with changes in the body shape while keeping the overall volume constant. In this study, we employed a marker-less optical tracking strategy to quantitatively study introvert protrusion (i.e. kinematics, elongation percentage and forces exerted) in different navigation media. WhenP.stephensonispecimens were free in sea water (outside from the burrow), the worms reached lengths up to three times their initial ones after protrusion. Moreover, they were able to elongate their introvert inside a viscous medium such as agar-based hydrogel. In this case, the organisms were able to break the hydrogel material, exerting forces up to 3 N and then to navigate easily inside it, producing stresses of some tens of kPa. Our measurements can be used as guidelines and specifications to design and develop novel smart robotic systems.

A Taxonomy for Mobile Robots: Types, Applications, Capabilities, Implementations, Requirements, and Challenges

Mobile robotics is a widespread field of research, whose differentiation from general robotics is often based only on the ability to move. However, mobile robots need unique capabilities, such as the function of navigation. Also, there are limiting factors, such as the typically limited energy, which must be considered when developing a mobile robot. This article deals with the definition of an archetypal robot, which is represented in the form of a taxonomy. Types and fields of application are defined. A systematic literature review is carried out for the definition of typical capabilities and implementations, where reference systems, textbooks, and literature references are considered.

Programmable and Self-Healing Light-Driven Actuators through Synergetic Use of Water-Shaping and -Welding Methods

Shape programming is critical for the fabrication of a light-driven actuator with complex shape morphing, which demonstrates potential applications in remote-controlled light-driven soft robots. However, it remains a huge challenge to obtain light-driven actuators having advantages of complex shape morphing, self-healing function, and facile fabrication simultaneously. Here, we report a facile strategy to obtain programmable and self-healing light-driven actuators with complex shape morphing. Various initial shapes of actuators can be programmed by synergetic use of water-shaping and -welding methods, which provides unlimited opportunities for fabricating actuators with predesigned shapes and subsequently demonstrating complex shape morphing. A template transfer method is used to prepare a single-layer graphene oxide (GO) film with asymmetric surface structures, which acts as the basic actuator and has the self-healing function based on the hydrophilic property of GO. It shows bending morphing under near-infrared (NIR) light irradiation due to the photothermal effect and asymmetric morphology on the opposite surfaces. Four more types of actuators are programmed from the basic actuator through the water-shaping method, which exhibits bending, unbending, twisting, and untwisting, respectively, under NIR light illumination. In addition, an S-shape actuator and a flower-shape actuator are programmed from the basic actuators through the water-welding method. By simply turning over the S-shape actuator, it can perform a bidirectional crawling motion. Finally, two intricate bionic light-driven actuators (tendril-shape and octopus-shape) are constructed, which are unattainable from conventional fabrication methods of actuators. We believe that this study will unlock a new way to programmable, self-healing, and light-driven soft robots with tunable and complex shape morphing.

Magnetic movement under the spotlight

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

A biomimetic soft robotic pinna for emulating dynamic reception behavior of horseshoe bats

Encoding of sensory information is fundamental to closing the performance gap between man-made and biological sensing. It has been hypothesized that the coupling of sensing and actuation, a phenomenon observed in bats among other species, is critical to accomplishing this. Using horseshoe bats as a model, we have developed a biomimetic pinna model with a soft actuation system along with a prototype strain sensor for enabling motor feedback. The actuation system used three individually controlled pneumatic actuators per pinna which actuated different portions of the baffle. This prototype produced eight different possible motions that were shown to have significant effects on incoming sound and could hence function as a substrate for adaptive sensing. The range of possible motions could be expanded by adjusting the fill and release parameters of the actuation system. Additionally, the strain sensor was able to represent the deformation of the pinna as measurements from this sensor were highly correlated with deformation estimates based on stereo vision. However, the relationship between displacements of points on the pinna and the sensor output was nonlinear. The improvements embodied in the system discussed here could lead to enhancements in the ability of autonomous systems to encode relevant information about the real world.

Fluidic Patch Device to Sample Sweat for Accurate Measurement of Sweat Rate and Chemical Composition: A Proof-of-Concept Study

Sweat sensors that can continuously sample sweat are critical for determining the time-dependent physiological responses occurring in normal daily life. Here, a new device, termed fluidic patch, for collecting human sweat samples at defined time intervals is developed, and the proof-of-concept is demonstrated. The device comprises micropumps and a disposable microfluidic patch attached to the human skin. The fluidic patch continuously collects aliquots of freshly secreted sweat accumulated in the fluidic pathway at accurately defined time windows (typically 5 min). By measuring the weight of the collected samples, the local sweat rate is calculated. The sweat sample collected can be directly subjected to a wide range of chemical analyses. For the proof-of-concept, we compared the sweat rates during passive heating in human trials using the fluidic patch and the conventional ventilated sweat capsule system. Although the sweat rate obtained using the fluidic patch highly correlated with that of the ventilated sweat capsule (R² = 0.96, y = 1.4x - 0.05), the fluidic patch overestimated the sweat rate compared with the ventilated capsule system when the sweat rate exceeded 0.5 mg/(cm²·min). The sampled sweat was analyzed for sodium, potassium, chloride, lactate, pyruvate, and cortisol. The device could obtain the time courses of the concentrations of the abovementioned three ions; the concentrations of sodium and chloride increased linearly with the sweat rate during passive heating (R² = 0.76 and 0.66, respectively). The device can reliably measure the sweat rate and collect sweat samples for chemical analysis. It can be utilized for real-time physiological investigations toward wider applications.

Coordinating attention requires coordinated senses

From playing basketball to ordering at a food counter, we frequently and effortlessly coordinate our attention with others towards a common focus: we look at the ball, or point at a piece of cake. This non-verbal coordination of attention plays a fundamental role in our social lives: it ensures that we refer to the same object, develop a shared language, understand each other's mental states, and coordinate our actions. Models of joint attention generally attribute this accomplishment to gaze coordination. But are visual attentional mechanisms sufficient to achieve joint attention, in all cases? Besides cases where visual information is missing, we show how combining it with other senses can be helpful, and even necessary to certain uses of joint attention. We explain the two ways in which non-visual cues contribute to joint attention: either as enhancers, when they complement gaze and pointing gestures in order to coordinate joint attention on visible objects, or as modality pointers, when joint attention needs to be shifted away from the whole object to one of its properties, say weight or texture. This multisensory approach to joint attention has important implications for social robotics, clinical diagnostics, pedagogy and theoretical debates on the construction of a shared world.

Thermal Infrared Sensing for Near Real-Time Data-Driven Fire Detection and Monitoring Systems

With the increasing interest in leveraging mobile robotics for fire detection and monitoring arises the need to design recognition technology systems for these extreme environments. This work focuses on evaluating the sensing capabilities and image processing pipeline of thermal imaging sensors for fire detection applications, paving the way for the development of autonomous systems for early warning and monitoring of fire events. The contributions of this work are threefold. First, we overview image processing algorithms used in thermal imaging regarding data compression and image enhancement. Second, we present a method for data-driven thermal imaging analysis designed for fire situation awareness in robotic perception. A study is undertaken to test the behavior of the thermal cameras in controlled fire scenarios, followed by an in-depth analysis of the experimental data, which reveals the inner workings of these sensors. Third, we discuss key takeaways for the integration of thermal cameras in robotic perception pipelines for autonomous unmanned aerial vehicle (UAV)-based fire surveillance.

Mobile robotic platforms for the acoustic tracking of deep-sea demersal fishery resources

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 programs (e.g., European Community H2020, as part of the Blue Growth economic strategy). However, such information is currently scarce, and high-frequency and prolonged data collection is rarely available. Here, we report the implementation of autonomous underwater vehicles and remotely operated vehicles as an aid for acoustic long-baseline localization systems for autonomous tracking of Norway lobster (Nephrops norvegicus), one of the key living resources exploited in European waters. In combination with seafloor moored acoustic receivers, we detected and tracked the movements of 33 tagged lobsters at 400-m depth for more than 3 months. We also identified the best procedures to localize both the acoustic receivers and the tagged lobsters, based on algorithms designed for off-the-shelf acoustic tags identification. Autonomous mobile platforms that deliver data on animal behavior beyond traditional fixed platform capabilities represent an advance for prolonged, in situ monitoring of deep-sea benthic animal behavior at meter spatial scales.

Recent advances in bioelectronics chemistry

Research in bioelectronics is highly interdisciplinary, with many new developments being based on techniques from across the physical and life sciences. Advances in our understanding of the fundamental chemistry underlying the materials used in bioelectronic applications have been a crucial component of many recent discoveries. In this review, we highlight ways in which a chemistry-oriented perspective may facilitate novel and deep insights into both the fundamental scientific understanding and the design of materials, which can in turn tune the functionality and biocompatibility of bioelectronic devices. We provide an in-depth examination of several developments in the field, organized by the chemical properties of the materials. We conclude by surveying how some of the latest major topics of chemical research may be further integrated with bioelectronics.

Spray-on magnetic skin for robotic actuation

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

Robust state dependent Riccati equation variable impedance control for robotic force-tracking tasks

Industrial robots are increasingly used in highly flexible interaction tasks, where the intrinsic variability makes difficult to pre-program the manipulator for all the different scenarios. In such applications, interaction environments are commonly (partially) unknown to the robot, requiring the implemented controllers to take in charge for the stability of the interaction. While standard controllers are sensor-based, there is a growing need to make sensorless robots (i.e., most of the commercial robots are not equipped with force/torque sensors) able to sense the environment, properly reacting to the established interaction. This paper proposes a new methodology to sensorless force control manipulators. On the basis of sensorless Cartesian impedance control, an Extended Kalman Filter (EKF) is designed to estimate the interaction exchanged between the robot and the environment. Such an estimation is then used in order to close a robust high-performance force loop, designed exploiting a variable impedance control and a State Dependent Riccati Equation (SDRE) force controller. The described approach has been validated in simulations. A Franka EMIKA panda robot has been considered as a test platform. A probing task involving different materials (i.e., with different stiffness properties) has been considered to show the capabilities of the developed EKF (able to converge with limited errors) and controller (preserving stability and avoiding overshoots). The proposed controller has been compared with an LQR controller to show its improved performance.

Biosynthetic self-healing materials for soft machines

Self-healing materials are indispensable for soft actuators and robots that operate in dynamic and real-world environments, as these machines are vulnerable to mechanical damage. However, current self-healing materials have shortcomings that limit their practical application, such as low healing strength (below a megapascal) and long healing times (hours). Here, we introduce high-strength synthetic proteins that self-heal micro- and macro-scale mechanical damage within a second by local heating. These materials are optimized systematically to improve their hydrogen-bonded nanostructure and network morphology, with programmable healing properties (2-23 MPa strength after 1 s of healing) that surpass by several orders of magnitude those of other natural and synthetic soft materials. Such healing performance creates new opportunities for bioinspired materials design, and addresses current limitations in self-healing materials for soft robotics and personal protective equipment.

Water strider females use individual experience to adjust jumping behaviour to their weight within physical constraints of water surface tension

Different species of water striders match leg speeds to their body sizes to maximize their jump take off velocity without breaking the water surface, which might have aided evolution of leg structures optimized for exploitation of the water surface tension. It is not understood how water striders achieve this match. Can individuals modify their leg movements based on their body mass and locomotor experience? Here we tested if water striders, Gerris latiabdominis, adjust jumping behaviour based on their personal experience and how an experimentally added body weight affects this process. Females, but not males, modified their jumping behaviour in weight-dependent manner, but only when they experienced frequent jumping. They did so within the environmental constraint set by the physics of water surface tension. Females' ability to adjust jumping may represent their adaptation to frequent increases or decreases of the weight that they support as mating bouts, during which males ride on top of females, start or end, respectively. This suggests that natural selection for optimized biomechanics combined with sexual selection for mating adaptations shapes this ability to optimally exploit water surface tension, which might have aided adaptive radiation of Gerromorpha into a diversity of semiaquatic niches.

Swimming statistics of cargo-loaded single bacteria

Burgeoning interest in the area of bacteria-powered micro robotic systems prompted us to study the dynamics of cargo transport by single bacteria. In this paper, we have studied the swimming behaviour of oil-droplets attached as cargo to the cell bodies of single bacteria. The oil-droplet loaded bacteria exhibit super-diffusive motion which is characterised by a high degree of directional persistence. Interestingly, bacteria could navigate with cargo size as large as 8 μm resulting in an increased rotational drag of more than 2 orders when compared to the free bacteria. The directional change of cargo loaded bacterial trajectories seems to be enhanced by steric hindrance from other oil-droplets present in the environment.

6D Virtual Sensor for Wrench Estimation in Robotized Interaction Tasks Exploiting Extended Kalman Filter

Industrial robots are commonly used to perform interaction tasks (such as assemblies or polishing), requiring the robot to be in contact with the surrounding environment. Such environments are (partially) unknown to the robot controller. Therefore, there is the need to implement interaction controllers capable of suitably reacting to the established contacts. Although standard force controllers require force/torque measurements to close the loop, most of the industrial manipulators do not have installed force/torque sensor(s). In addition, the integration of external sensors results in additional costs and implementation effort, not affordable in many contexts/applications. To extend the use of compliant controllers to sensorless interaction control, a model-based methodology is presented in this paper for the online estimation of the interaction wrench, implementing a 6D virtual sensor. Relying on sensorless Cartesian impedance control, an Extended Kalman Filter (EKF) is proposed for the interaction wrench estimation. The described approach has been validated in simulations, taking into account four different scenarios. In addition, experimental validation has been performed employing a Franka EMIKA panda robot. A human–robot interaction scenario and an assembly task have been considered to show the capabilities of the developed EKF, which is able to perform the estimation with high bandwidth, achieving convergence with limited errors.