RESUMO
In the amusing 1982 novel Software, robots punish their human overlords by raising prices on longevity drugs and organ transplants.
Assuntos
Robótica , Software , Robótica/instrumentação , Robótica/estatística & dados numéricos , Humanos , Preparações Farmacêuticas , Transplante de Órgãos/instrumentação , Longevidade , História do Século XXRESUMO
The OpenFlexure Microscope is an accessible, three-dimensional-printed robotic microscope, with sufficient image quality to resolve diagnostic features including parasites and cancerous cells. As access to lab-grade microscopes is a major challenge in global healthcare, the OpenFlexure Microscope has been developed to be manufactured, maintained and used in remote environments, supporting point-of-care diagnosis. The steps taken in transforming the hardware and software from an academic prototype towards an accepted medical device include addressing technical and social challenges, and are key for any innovation targeting improved effectiveness in low-resource healthcare. This article is part of the Theo Murphy meeting issue 'Open, reproducible hardware for microscopy'.
Assuntos
Microscopia , Microscopia/instrumentação , Microscopia/métodos , Humanos , Robótica/instrumentação , Robótica/tendências , Robótica/estatística & dados numéricos , Desenho de Equipamento , Impressão Tridimensional/instrumentação , Atenção à Saúde , Software , Sistemas Automatizados de Assistência Junto ao LeitoRESUMO
To enhance wearable robots, understanding user intent and environmental perception with novel vision approaches is needed.
Assuntos
Robótica , Dispositivos Eletrônicos Vestíveis , Robótica/instrumentação , Robótica/tendências , Robótica/estatística & dados numéricos , Humanos , Desenho de Equipamento , Inteligência Artificial , IntençãoRESUMO
BACKGROUND: As the disabled population ages and the demand for care increases, Socially, the need for care robots is emerging but, perceptions of care robots among care recipients is unknown. PURPOSE: To determine the level of intention to use care robots among care recipients and identify predictors of intention to use care robots. METHODS: A cross-sectional survey was conducted using a convenience sample of 163 persons with disabilities from January to March 2022 at the Veterans Health Service Medical Center. DISCUSSION: Overall, 64.42% of respondents intended to use care robots. Predictors included perceived behavioral control, participants' perceptions of the caregiver's burden, attitude toward robot use, subjective norms, and age. CONCLUSION: These findings suggest that individuals who are community-dwelling desire the use care robots to maintain their independence and may provide useful insignt for the introduction various care robots in acute care and long-term care settings.
Assuntos
Pessoas com Deficiência , Intenção , Robótica , Humanos , Masculino , Estudos Transversais , Feminino , Robótica/estatística & dados numéricos , Pessoa de Meia-Idade , Pessoas com Deficiência/psicologia , Pessoas com Deficiência/estatística & dados numéricos , Adulto , Idoso , Inquéritos e Questionários , Estados Unidos , Cuidadores/psicologia , Cuidadores/estatística & dados numéricos , Idoso de 80 Anos ou maisRESUMO
Legged robots that can operate autonomously in remote and hazardous environments will greatly increase opportunities for exploration into underexplored areas. Exteroceptive perception is crucial for fast and energy-efficient locomotion: Perceiving the terrain before making contact with it enables planning and adaptation of the gait ahead of time to maintain speed and stability. However, using exteroceptive perception robustly for locomotion has remained a grand challenge in robotics. Snow, vegetation, and water visually appear as obstacles on which the robot cannot step or are missing altogether due to high reflectance. In addition, depth perception can degrade due to difficult lighting, dust, fog, reflective or transparent surfaces, sensor occlusion, and more. For this reason, the most robust and general solutions to legged locomotion to date rely solely on proprioception. This severely limits locomotion speed because the robot has to physically feel out the terrain before adapting its gait accordingly. Here, we present a robust and general solution to integrating exteroceptive and proprioceptive perception for legged locomotion. We leverage an attention-based recurrent encoder that integrates proprioceptive and exteroceptive input. The encoder is trained end to end and learns to seamlessly combine the different perception modalities without resorting to heuristics. The result is a legged locomotion controller with high robustness and speed. The controller was tested in a variety of challenging natural and urban environments over multiple seasons and completed an hour-long hike in the Alps in the time recommended for human hikers.
Assuntos
Locomoção/fisiologia , Robótica/instrumentação , Materiais Biomiméticos , Biomimética , Simulação por Computador , Meio Ambiente , Marcha/fisiologia , Humanos , Aprendizado de Máquina , Modelos Biológicos , Redes Neurais de Computação , Propriocepção/fisiologia , Robótica/estatística & dados numéricos , Estações do Ano , Caminhada/fisiologiaRESUMO
The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had severe consequences for health and the global economy. To control the transmission, there is an urgent demand for early diagnosis and treatment in the general population. In the present study, an automatic system for SARS-CoV-2 diagnosis is designed and built to deliver high specification, high sensitivity, and high throughput with minimal workforce involvement. The system, set up with cross-priming amplification (CPA) rather than conventional reverse transcription-polymerase chain reaction (RT-PCR), was evaluated using more than 1000 real-world samples for direct comparison. This fully automated robotic system performed SARS-CoV-2 nucleic acid-based diagnosis with 192 samples in under 180 min at 100 copies per reaction in a "specimen in data out" manner. This throughput translates to a daily screening capacity of 800-1000 in an assembly-line manner with limited workforce involvement. The sensitivity of this device could be further improved using a CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)-based assay, which opens the door to mixed samples, potentially include SARS-CoV-2 variants screening in extensively scaled testing for fighting COVID-19.
Assuntos
Teste de Ácido Nucleico para COVID-19/métodos , COVID-19/diagnóstico , SARS-CoV-2 , Algoritmos , Engenharia Biomédica/instrumentação , Engenharia Biomédica/métodos , Engenharia Biomédica/estatística & dados numéricos , COVID-19/epidemiologia , COVID-19/virologia , Teste de Ácido Nucleico para COVID-19/instrumentação , Teste de Ácido Nucleico para COVID-19/estatística & dados numéricos , Repetições Palindrômicas Curtas Agrupadas e Regularmente Espaçadas , Desenho de Equipamento , Ensaios de Triagem em Larga Escala/instrumentação , Ensaios de Triagem em Larga Escala/métodos , Ensaios de Triagem em Larga Escala/estatística & dados numéricos , Humanos , Técnicas de Amplificação de Ácido Nucleico/instrumentação , Técnicas de Amplificação de Ácido Nucleico/métodos , Técnicas de Amplificação de Ácido Nucleico/estatística & dados numéricos , Pandemias , Robótica/instrumentação , Robótica/métodos , Robótica/estatística & dados numéricos , SARS-CoV-2/genética , Sensibilidade e Especificidade , Análise de SistemasRESUMO
Understanding the human motor control strategy during physical interaction tasks is crucial for developing future robots for physical human-robot interaction (pHRI). In physical human-human interaction (pHHI), small interaction forces are known to convey their intent between the partners for effective motor communication. The aim of this work is to investigate what affects the human's sensitivity to the externally applied interaction forces. The hypothesis is that one way the small interaction forces are sensed is through the movement of the arm and the resulting proprioceptive signals. A pHRI setup was used to provide small interaction forces to the hand of seated participants in one of four directions, while the participants were asked to identify the direction of the push while blindfolded. The result shows that participants' ability to correctly report the direction of the interaction force was lower with low interaction force as well as with high muscle contraction. The sensitivity to the interaction force direction increased with the radial displacement of the participant's hand from the initial position: the further they moved the more correct their responses were. It was also observed that the estimated stiffness of the arm varies with the level of muscle contraction and robot interaction force.
Assuntos
Propriocepção/fisiologia , Robótica/métodos , Interface Usuário-Computador , Adolescente , Adulto , Braço/fisiologia , Fenômenos Biomecânicos , Feminino , Mãos/fisiologia , Humanos , Modelos Lineares , Masculino , Modelos Biológicos , Movimento/fisiologia , Contração Muscular/fisiologia , Robótica/instrumentação , Robótica/estatística & dados numéricos , Adulto JovemRESUMO
BACKGROUND AND AIM: Loneliness is a common problem in older adults and contributes to poor health. This scoping review aimed to synthesize and report evidence on the effectiveness of interventions using social robots or computer agents to reduce loneliness in older adults and to explore intervention strategies. METHODS: The review adhered to the Arksey and O'Malley process for conducting scoping reviews. The SCOPUS, PUBMED, Web of Science, EMBASE, CINAHL, PsycINFO, ACM Digital Library and IEEE Xplore databases were searched in November, 2020. A two-step selection process identified eligible research. Information was extracted from papers and entered into an Excel coding sheet and summarised. Quality assessments were conducted using the Mixed Methods Appraisal Tool. RESULTS: Twenty-nine studies were included, of which most were of moderate to high quality. Eighteen were observational and 11 were experimental. Twenty-four used robots, four used computer agents and one study used both. The majority of results showed that robots or computer agents positively impacted at least one loneliness outcome measure. Some unintended negative consequences on social outcomes were reported, such as sadness when the robot was removed. Overall, the interventions helped to combat loneliness by acting as a direct companion (69%), a catalyst for social interaction (41%), facilitating remote communication with others (10%) and reminding users of upcoming social engagements (3%). CONCLUSION: Evidence to date suggests that robots can help combat loneliness in older adults, but there is insufficient research on computer agents. Common strategies for reducing loneliness include direct companionship and enabling social interactions. Future research could investigate other strategies used in human interventions (eg, addressing maladaptive social cognition and improving social skills), and the effects of design features on efficacy. It is recommended that more robust experimental and mixed methods research be conducted, using a combination of validated self-report, observational, and interview measures of loneliness.
Assuntos
Envelhecimento/psicologia , Alfabetização Digital/estatística & dados numéricos , Solidão/psicologia , Robótica/estatística & dados numéricos , Isolamento Social/psicologia , Adaptação Psicológica , Idoso , Amigos/psicologia , Humanos , Relações Interpessoais , MasculinoRESUMO
Human skin can sense subtle changes of both normal and shear forces (i.e., self-decoupled) and perceive stimuli with finer resolution than the average spacing between mechanoreceptors (i.e., super-resolved). By contrast, existing tactile sensors for robotic applications are inferior, lacking accurate force decoupling and proper spatial resolution at the same time. Here, we present a soft tactile sensor with self-decoupling and super-resolution abilities by designing a sinusoidally magnetized flexible film (with the thickness ~0.5 millimeters), whose deformation can be detected by a Hall sensor according to the change of magnetic flux densities under external forces. The sensor can accurately measure the normal force and the shear force (demonstrated in one dimension) with a single unit and achieve a 60-fold super-resolved accuracy enhanced by deep learning. By mounting our sensor at the fingertip of a robotic gripper, we show that robots can accomplish challenging tasks such as stably grasping fragile objects under external disturbance and threading a needle via teleoperation. This research provides new insight into tactile sensor design and could be beneficial to various applications in robotics field, such as adaptive grasping, dexterous manipulation, and human-robot interaction.
Assuntos
Órgãos Artificiais , Mãos , Robótica/instrumentação , Pele , Tato , Materiais Biomiméticos , Módulo de Elasticidade , Elastômeros , Humanos , Aprendizado de Máquina , Fenômenos Magnéticos , Fenômenos Mecânicos , Robótica/estatística & dados numéricos , Materiais InteligentesRESUMO
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 cut pattern is determined by evaluating the shell's mechanics and geometry, using a combination of experiments, finite element simulations, and theoretical modeling, which enables the gripper design to be both scalable and material independent. We demonstrate that the kirigami shell gripper can be readily integrated with an existing robotic platform or remotely actuated using a magnetic field. The kirigami cut pattern results in a simple unit cell that can be connected together in series, and again in parallel, to create kirigami gripper arrays capable of simultaneously grasping multiple delicate and slippery objects. These soft and lightweight grippers will have applications in robotics, haptics, and biomedical device design.
Assuntos
Força da Mão/fisiologia , Robótica/instrumentação , Materiais Inteligentes , Bioengenharia , Materiais Biomiméticos , Simulação por Computador , Desenho de Equipamento , Análise de Elementos Finitos , Humanos , Campos Magnéticos , Fenômenos Mecânicos , Microtecnologia , Polietilenotereftalatos , Robótica/estatística & dados numéricos , Polímeros Responsivos a Estímulos , Resistência à TraçãoRESUMO
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 addition, with the development of better simulation environments, we can generate and study scenarios that allow for benchmarking of various approaches and gain better understanding of what theoretical developments need to be made and how practical systems can be implemented and evaluated to provide flexible, scalable, and robust solutions. To this end, we survey more than 100 relevant studies in this area and use it as the basis to discuss open problems. We adopt a learning perspective to unify the discussion over analytical and data-driven approaches, addressing how to use and integrate model priors and task data in perceiving and manipulating a variety of deformable objects.
Assuntos
Robótica/métodos , Simulação por Computador , Humanos , Aprendizagem , Fenômenos Mecânicos , Percepção , Fenômenos Físicos , Robótica/instrumentação , Robótica/estatística & dados numéricosRESUMO
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 necessary model parameters using minimal sensing. Here, we derive algorithms, on the basis of the concept of virtual linkage-based representations (VLRs), to self-identify the underlying mechanics of hand-object systems via exploratory manipulation actions and probabilistic reasoning and, in turn, show that the self-identified VLR can enable the control of precise in-hand manipulation. To validate our framework, we instantiated the proposed system on a Yale Model O hand without joint encoders or tactile sensors. The passive adaptability of the underactuated hand greatly facilitates the self-identification process, because they naturally secure stable hand-object interactions during random exploration. Relying solely on an in-hand camera, our system can effectively self-identify the VLRs, even when some fingers are replaced with novel designs. In addition, we show in-hand manipulation applications of handwriting, marble maze playing, and cup stacking to demonstrate the effectiveness of the VLR in precise in-hand manipulation control.
Assuntos
Mãos , Robótica/métodos , Algoritmos , Fenômenos Biomecânicos , Simulação por Computador , Desenho de Equipamento , Força da Mão , Interface Háptica/estatística & dados numéricos , Humanos , Sistemas Homem-Máquina , Robótica/instrumentação , Robótica/estatística & dados numéricos , Teoria de Sistemas , Interface Usuário-ComputadorRESUMO
Policy gradient methods can be used for mechanical and computational co-design of robot manipulators.
Assuntos
Mãos , Robótica/instrumentação , Simulação por Computador , Desenho de Equipamento , Humanos , Fenômenos Mecânicos , Destreza Motora , Robótica/estatística & dados numéricosRESUMO
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 for an independently loaded synchronized dual-catapult system. To power the ballistic movement of a single specialized mouthpart, two independently loaded springs simultaneously release and actuate two separate joints in a kinematic chain. Energy for the movement is stored by straining an elastic structure at each joint and, possibly, the surrounding cuticle, which is preloaded by muscle contraction. As a proof of concept, we developed a bioinspired robotic model resembling the morphology and functional principle of the extensible mouthpart. Understanding the biomechanics of the independently loaded synchronized dual-catapult system found in dragonfly larvae can be used to control the extension direction and, thereby, thrust vector of a power-modulated robotic system.
Assuntos
Odonatos/fisiologia , Robótica/instrumentação , Animais , Fenômenos Biomecânicos , Materiais Biomiméticos , Comportamento Alimentar/fisiologia , Larva/anatomia & histologia , Larva/fisiologia , Modelos Biológicos , Boca/anatomia & histologia , Boca/fisiologia , Movimento/fisiologia , Odonatos/anatomia & histologia , Comportamento Predatório/fisiologia , Robótica/estatística & dados numéricosRESUMO
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. We use this system to experimentally demonstrate that resonance greatly benefits pulse-jet swimming speed and efficiency, and the robot's optimal cost of transport is found to match that of the most efficient biological swimmers in nature, such as the jellyfish Aurelia aurita The robot also exhibits a preferred Strouhal number for efficient swimming, thereby bridging the gap between pulse-jet propulsion and established findings in efficient fish swimming. Extensions of the current robotic framework to larger amplitude oscillations could combine resonance effects with optimal vortex formation to further increase propulsive performance and potentially outperform biological swimmers altogether.
Assuntos
Decapodiformes/fisiologia , Robótica/instrumentação , Natação/fisiologia , Animais , Fenômenos Biomecânicos , Materiais Biomiméticos , Decapodiformes/anatomia & histologia , Desenho de Equipamento , Modelos Biológicos , Robótica/estatística & dados numéricos , Cifozoários/fisiologia , VibraçãoRESUMO
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 arise from visual observations of nearby neighbors, without explicit communication. By contrast, most underwater robot collectives rely on centralized, above-water, explicit communication and, as a result, exhibit limited coordination complexity. Here, we demonstrate 3D collective behaviors with a swarm of fish-inspired miniature underwater robots that use only implicit communication mediated through the production and sensing of blue light. We show that complex and dynamic 3D collective behaviors-synchrony, dispersion/aggregation, dynamic circle formation, and search-capture-can be achieved by sensing minimal, noisy impressions of neighbors, without any centralized intervention. Our results provide insights into the power of implicit coordination and are of interest for future underwater robots that display collective capabilities on par with fish schools for applications such as environmental monitoring and search in coral reefs and coastal environments.
Assuntos
Peixes/fisiologia , Robótica/instrumentação , Comunicação Animal , Animais , Comportamento Animal/fisiologia , Simulação por Computador , Desenho de Equipamento , Luz , Fenômenos Mecânicos , Modelos Biológicos , Movimento , Percepção , Robótica/estatística & dados numéricos , Comportamento Social , Natação/fisiologiaRESUMO
BACKGROUND: Robot-assisted therapy and noninvasive brain stimulation (NIBS) are promising strategies for stroke rehabilitation. OBJECTIVE: This systematic review and meta-analysis aims to evaluate the evidence of NIBS as an add-on intervention to robotic therapy in order to improve outcomes of upper-limb motor impairment or activity in individuals with stroke. METHODS: This study was performed according to the PRISMA Protocol and was previously registered on the PROSPERO Platform (CRD42017054563). Seven databases and gray literature were systematically searched by 2 reviewers, and 1176 registers were accessed. Eight randomized clinical trials with upper-limb body structure/function or activity limitation outcome measures were included. Subgroup analyses were performed according to phase poststroke, device characteristics (ie, arm support, joints involved, unimanual or bimanual training), NIBS paradigm, timing of stimulation, and number of sessions. The Grade-Pro Software was used to assess quality of the evidence. RESULTS: A nonsignificant homogeneous summary effect size was found both for body structure function domain (mean difference [MD] = 0.15; 95% CI = -3.10 to 3.40; P = 0.93; I2 = 0%) and activity limitation domain (standard MD = 0.03; 95% CI = -0.28 to 0.33; P = 0.87; I2 = 0%). CONCLUSIONS: According to this systematic review and meta-analysis, at the moment, there are not enough data about the benefits of NIBS as an add-on intervention to robot-assisted therapy on upper-limb motor function or activity in individuals with stroke.
Assuntos
Avaliação de Resultados em Cuidados de Saúde , Ensaios Clínicos Controlados Aleatórios como Assunto , Robótica , Reabilitação do Acidente Vascular Cerebral , Acidente Vascular Cerebral/terapia , Terapia Assistida por Computador , Estimulação Transcraniana por Corrente Contínua , Estimulação Magnética Transcraniana , Extremidade Superior , Humanos , Avaliação de Resultados em Cuidados de Saúde/estatística & dados numéricos , Ensaios Clínicos Controlados Aleatórios como Assunto/estatística & dados numéricos , Robótica/estatística & dados numéricos , Acidente Vascular Cerebral/fisiopatologia , Reabilitação do Acidente Vascular Cerebral/estatística & dados numéricos , Terapia Assistida por Computador/estatística & dados numéricos , Estimulação Transcraniana por Corrente Contínua/estatística & dados numéricos , Estimulação Magnética Transcraniana/estatística & dados numéricos , Extremidade Superior/fisiopatologiaRESUMO
Traffic congestion is monotonically increasing, especially in large cities, due to rapid urbanization. Traffic congestion not only deteriorates traffic operation and degrades traffic safety, but also imposes costs to the road users. The concerns associated with traffic congestion increase when considering more complicated situations such as unsignalized intersections and driveways at which maneuvers are entirely dependent upon drivers' judgment. Urban arterials are characterized by closely spaced signalized and unsignalized intersections and high traffic volumes, which make them a priority while analyzing traffic safety and operation. Autonomous Vehicles (AV) provide ample opportunities to overcome the aforementioned challenges. In essence, this study evaluates the impact of various AV Market Penetration Rates (MPR) on the safety and operation of urban arterials in proximity of a driveway under different traffic levels of service (LOS). Twenty-four separate scenarios were developed using VISSIM, considering six AV MPRs of 0 %, 10 %, 25 %, 50 %, 75 %, and 100 %, and four LOS including A, B, C, and D. Various operational and safety measures were analyzed including traffic density, traffic speed, traffic conflict (rear-end and lane-changing), and driving volatility. The trajectory and lane-based analysis of the traffic density indicates that MPR significantly improves the overall traffic density for all the scenarios, especially under high traffic LOS. Additionally, by increasing the MPR and decreasing the traffic volume of the network, the mean speed increases significantly by up to 6 %. Exploring the safety of the scenarios indicates that by increasing the MPR from 0% to 100 % for all the LOS, the number of rear-end conflicts and lane-changing conflicts decreases 84 %-100 % and 42 %-100 %, respectively. Moreover, assessing the longitudinal driving volatility measures, which represent risky driving behaviors, showed that higher MPRs significantly reduce some of the driving volatility measures and enhance safety.
Assuntos
Acidentes de Trânsito/estatística & dados numéricos , Condução de Veículo/estatística & dados numéricos , Automóveis/estatística & dados numéricos , Planejamento de Cidades , Planejamento Ambiental , Robótica/estatística & dados numéricos , Segurança/estatística & dados numéricos , Acidentes de Trânsito/prevenção & controle , HumanosRESUMO
This paper presents a computer simulation of a virtual robot that behaves as a peptide chain of the Hemagglutinin-Esterase protein (HEs) from human coronavirus. The robot can learn efficient protein folding policies by itself and then use them to solve HEs folding episodes. The proposed robotic unfolded structure inhabits a dynamic environment and is driven by a self-taught neural agent. The neural agent can read sensors and control the angles and interactions between individual amino acids. During the training phase, the agent uses reinforcement learning to explore new folding forms that conduce toward more significant rewards. The memory of the agent is implemented with neural networks. These neural networks are noise-balanced trained to satisfy the look for future conditions required by the Bellman equation. In the operating phase, the components merge into a wise up protein folding robot with look-ahead capacities, which consistently solves a section of the HEs protein.
Assuntos
Dobramento de Proteína , Robótica/métodos , Algoritmos , Sequência de Aminoácidos , Simulação por Computador , Coronavirus/química , Hemaglutininas Virais/química , Humanos , Aprendizado de Máquina , Modelos Moleculares , Redes Neurais de Computação , Conformação Proteica , Robótica/estatística & dados numéricos , Análise de Sistemas , Biologia de Sistemas , Proteínas Virais de Fusão/química , Proteínas Virais/químicaRESUMO
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, realizing multiple modalities in a soft sensor without increasing its original form factor is beneficial, because even a single input stimulus to a robot may induce a combination of multiple modes of deformation. Here, we report a multifunctional soft sensor capable of decoupling combined deformation modes of stretching, bending, and compression, as well as detecting individual deformation modes, in a compact form factor. The key enabling design feature of the proposed sensor is a combination of heterogeneous sensing mechanisms: optical, microfluidic, and piezoresistive sensing. We characterize the performance on both detection and decoupling of deformation modes, by implementing both a simple algorithm of threshold evaluation and a machine learning technique based on an artificial neural network. The proposed soft sensor is able to estimate eight different deformation modes with accuracies higher than 95%. We lastly demonstrate the potential of the proposed sensor as a method of human-robot interfaces with several application examples highlighting its multifunctionality.