Application Of Humanoid Robot Research Articles

Development of depression assessment tools using humanoid robots -Can tele-operated robots talk with depressive persons like humans?

BackgroundDepression is a common mental disorder and causes significant social loss. Early intervention for depression is important. Nonetheless, depressed patients tend to conceal their symptoms from others based on shame and stigma, thus hesitate to visit psychiatrists especially during early phase.We hypothesize that application of humanoid robots would be a novel solution. Depressed patients may feel more comfortable talking with such robots than humans. MethodsWe recruited 13 patients with major depressive disorder (MDD) and 27 healthy volunteers as controls. Participants took both tele-operated humanoid robot and human interviews to evaluate severity of depression using the Hamilton Depression Rating Scale (HDRS). In addition, participants completed a self-administered questionnaire asking about their impressions of the robot interview. ResultsConfidence interval and t-test analysis have revealed that the HDRS scores are equally reliable between robot and human interviews. No significant differences were observed between the two interviews regarding “nervousness about the interview” and “hesitancy to talk about depressed moods and suicidal ideation.” Compared to human interviews, robot interviews yielded significantly lower scores on shame-related factors especially among patients with MDD. LimitationSmall sample size, and the evaluator is male only. ConclusionsThis is the first report to show the reliability of tele-operated humanoid robot interviews for assessment of depression. Robot interviews are potentially equally reliable as human interviews. Robot interviews are suggested to be more appropriate in assessing shame-related suppressed emotions and hidden thoughts of depressed patients in clinical practice, which may reduce the stigma associated with depression.

Touch, press and stroke: a soft capacitive sensor skin

Soft sensors that can discriminate shear and normal force could help provide machines the fine control desirable for safe and effective physical interactions with people. A capacitive sensor is made for this purpose, composed of patterned elastomer and containing both fixed and sliding pillars that allow the sensor to deform and buckle, much like skin itself. The sensor differentiates between simultaneously applied normal force and shear using summation and differences of signals from four deformable capacitors. Cross talk from shear to normal force is less than 2.5%, and between shear axes is less than 10%. Normal and shear stress sensitivity is 0.49 kPa and 0.31 kPa respectively, with a minimum displacement resolution of 40 μm. In addition, finger proximity is detectable at a range of up to 15 mm. The operation is demonstrated on a simple gripper holding a cup. The combination of features and the straightforward fabrication method make this sensor a candidate for implementation as a sensing skin for humanoid robotics applications.

Highly Elastic, Self-Healing, Recyclable Interlocking Double-Network Liquid-Free Ionic Conductive Elastomers via Facile Fabrication for Wearable Strain Sensors.

Liquid-free ionic conductive elastomers (ICEs) are ideal materials for wearable strain sensors in increasingly flexible electronic devices. However, developing recyclable ICEs with high elasticity, self-healability, and recyclability is still a great challenge. In this study, we fabricated a series of novel ICEs by in situ polymerization of lipoic acid (LA) in poly(acrylic acid) (PAA) solution and cross-linking by coordination bonding and hydrogen bonding. One of the obtained dynamically cross-linked interlocking double-network ICEs, PLA-PAA4-1% ICE, showed excellent mechanical properties, with high elasticity (90%) and stretchability (610%), as well as rapid self-healability (mechanical self-healing within 2 h and electrical recovery within 0.3 s). The PLA-PAA4-1% ICE was used as a strain sensor and possessed excellent linear sensitivity and highly cyclic stability, effectively monitoring diverse human motions with both stretched and compressed deformations. Notably, the PLA-PAA4-1% ICE can be fully recycled and reused as a new strain sensor without any structure change or degradation in performance. This work provided a viable path to fabricate conductive materials by solving the two contradictions of high mechanical property and self-healability, and structure stability and recyclability. We believe that the superior overall performance and feasible fabrication make the developed PLA-PAA4-1% ICE hold great promise as a multifunctional strain sensor for practical applications in flexible wearable electronic devices and humanoid robotics.

Understanding the Importance and Challenges of Animatronic Humanoid Prototypes Production in the Robotic Field in the United of States of America: Policy Implications

This study analyzes the importance and challenges of animatronic humanoid prototypes production within the robotic field in the United States of America to influence Artificial Intelligence (AI) policy. In fact, animatronic humanoid prototype has greatly inspired more designers and developers’ interest in the study of human and robot interaction in both scientists and enthusiast alike to aid in robotic production. The study adopted a narrative literature review and Boolean search technique to identify 22 researches and review articles that are related to applications, challenges and importance of animatronic humanoid robotics production and applications. As part of the findings for the study utilized for the article, many scholars made specific inferences to the robotic applications in firms, businesses, and nations. Out of the twenty-two articles, five of the researchers, thus 22%, underscored and also perceived that robots and machines with biped locomotion is one of the achievements of humanoid robotic production. Researchers of 4 articles—thus 18% -- explicitly stated in their research that one of the achievements of humanoid robotic production is “learning capabilities in robots”. The study further revealed that some of the evidenced-based research applications for humanoid robotic products include the following: Mitsuo Kawato of ATR Japan proposed using humanoid robots to study human behavior; In Europe- EU-funded projects, which include the large-scale NEUROBOTICS project; RobotCub project; Human Brain Project; Atlas humanoid robot by Boston Dynamics; and Wisdom of the robot Sophia in engaging in conversations, etc. Above all, this study revealed that complex environment, perception, human robot interaction, and collaboration in real life are some of the challenges identified in the literature. Therefore, in order to overcome such challenges—for the body of a robot, designers need to rethink the materials that robots are made of and leverage morphological computation to intrinsically balance and compensate for motion and dynamic behavior. Also, investors, policymakers, and public officials should invest more in innovative robotic production in order to promote businesses, bring about efficiency in operations, and to increase productivity. Keywords: Humanoid, Locomotion, Robots, Prototypes, Production, Animatronic, Boolean-Search, Jobs, Artificial Intelligence DOI: 10.7176/ISDE/13-1-02 Publication date: March 31 st 2023

An analysis and review of robot magic shows

Abstract The field of humanoid robotics is constantly evolving, with new advances creating exciting opportunities for research and development. Especially in the entertainment area, robotics applications show significant growth potential. To guide and track the progress of robotics research, good benchmark problems are crucial, but especially investigating human–robot interaction capabilities is difficult. This paper examines robot magic shows as a benchmark and research direction for entertainer robots and discusses flexible and versatile system architectures for robot magicians in the humanoid robot application challenge competition since 2017. The goal is a detailed analysis of magic tricks and magician robots presented in front of audiences. This paper reviews the hardware components and examines the robot platforms of participating teams in the robot magic show, the types of magic performances, the magic tricks and tools, the algorithms for the magic tricks, and the framework for humanoid robots. By providing a comprehensive analysis of these elements, we can gain insight into the capabilities of advanced humanoid robots for high-performance magic tricks. In conclusion, this paper highlights the exciting potential of humanoid robotics and entertainment fusion. In addition, we analyze the use of humanoid robots in magic shows, presenting the industrial potential of entertainer robots.

The Application of Interactive Humanoid Robots in the History Education of Museums Under Artificial Intelligence

The purpose is to improve the application of museum robots in museum scenes, enhance the service capabilities of robots in museums, break tourists’ boring concepts of museum environment, manual explanation, services, etc., and promote tourists’ exhibition experience. A method for sentiment analysis of humanoid robots in museums is proposed by studying the transformation of museums with the help of artificial intelligence (AI) technology, as well as the function and significance of museums in history education. First, the function of museums in history education and the role of AI in constructing intelligent museums are described. Second, on account of the multimodal sentiment analysis method of speech and emotion, a scenario model of the visitor museum is established. An uncertain reasoning method for robot service tasks based on Multi-entity Bayesian network (MEBN) is also proposed. Finally, the proposed model is validated by experiments. The results show that compared with the recognition rates of Arousal and Valence dimensions, the consistency correlation coefficient value of the Kalman filter is higher. The Consistency Correlation Coefficient (CCC) value of the Arousal dimension is 0.703, and the CCC value of the Valence dimension is 0.766. Besides, in different tour times, the proportion of services that tourists want to be provided with varies in different emotional states. From time t1 to time t2, the proportion of tourists who want to hear explanations of cultural relics dropped by 11.5%, while the proportion of tourists who want to be provided with tea service increased by 24%. This indicates that when the Kalman filter algorithm performs continuous emotion recognition of a multimodal fusion, the final emotion recognition accuracy is higher, and emotion analysis can help humanoid robots to be more intelligent and humanized. The proposed sentiment analysis based on the multimodal analysis and MEBN’s uncertainty reasoning method for robot service tasks not only broadens the practical application field of intelligent robots under human–computer interaction technology but also has important research significance for the innovative education development of museum history education.

Study on Musical Saw Bowing Motion with an Industrial Cooperative Humanoid Robot

The objective of this study was to automate the dual-arm coordination of an industrial humanoid robot when using a musical saw as a percussion instrument to produce a target sound. Especially, this report focuses on a humanoid robot with a characteristic of the real-time control to replace the traditional teaching and playback motion control. Meanwhile, it is assumed that the humanoid robot works in the environment that is near to a human being. To adapt in such situation, we aim to achieve the complex work using an advanced tool with its robot, as we perform a skillful motion. In the present report, we examine the performance of a musical saw using a bow because it is a kind of complex work using an unknown and advanced tool. Moreover, both the control method of the arm of the robot and the performance of the bow are discussed to construct a sound feedback control approach. As a result, it is demonstrated that the proposed approach has potential for both industrial and recreational applications of humanoid robots in human occupied environments.

Optimization of Dynamic Sit-to-Stand Trajectories to Assess Whole-Body Motion Performance of the Humanoid Robot REEM-C.

To enable the application of humanoid robots outside of laboratory environments, the biped must meet certain requirements. These include, in particular, coping with dynamic motions such as climbing stairs or ramps or walking over irregular terrain. Sit-to-stand transitions also belong to this category. In addition to their actual application such as getting out of vehicles or standing up after sitting, for example, at a table, these motions also provide benefits in terms of performance assessment. Therefore, they have long been used as a sports medical and geriatric assessment for humans. Here, we develop optimized sit-to-stand trajectories using optimal control, which are characterized by their dynamic and humanlike nature. We implement these motions on the humanoid robot REEM-C. Based on the obtained sensor data, we present a unified benchmarking procedure based on two different experimental protocols. These protocols are characterized by their increasing level of difficulty for quantifying different aspects of lower limb performance. We report performance results obtained by REEM-C using two categories of indicators: primary, scenario-specific indicators that assess overall performance (chair height and ankle-to-chair distance) and subsidiary, general indicators that further describe performance. The latter provide a more detailed analysis of the applied motion and are based on metrics such as the angular momentum, zero moment point, capture point, or foot placement estimator. In the process, we identify performance deficiencies of the robot based on the collected data. Thus, this work is an important step toward a unified quantification of bipedal performance in the execution of humanlike and dynamically demanding motions.

Bimodal Tactile Sensor without Signal Fusion for User-Interactive Applications

Tactile sensors with multimode sensing ability are cornerstones of artificial skin for applications in humanoid robotics and smart prosthetics. However, the intuitive and interference-free reading of multiple tactile signals without involving complex algorithms and calculations remains a challenge. Herein a pressure-temperature bimodal tactile sensor without any interference is demonstrated by combining the fundamentally different sensing mechanisms of optics and electronics, enabling the simultaneous and independent sensing of pressure and temperature with the elimination of signal separation algorithms and calculations. The bimodal sensor comprises a mechanoluminescent hybrid of ZnS-CaZnOS and a poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) thermoresistant material, endowing the unambiguous transduction of pressure and temperature into optical and electrical signals, respectively. This device exhibits the highest temperature sensitivity of -0.6% °C-1 in the range of 21-60 °C and visual sensing of the applied forces at a low limitation of 2 N. The interference-free and light-emitting characteristics of this device permit user-interactive applications in robotics for encrypted communication as well as temperature and pressure monitoring, along with wireless signal transmission. This work provides an unexplored solution to signal interference of multimodal tactile sensors, which can be extended to other multifunctional sensing devices.

Human-Humanoid Interaction and Cooperation: a Review

Humanoid robots are versatile platforms with the potential to assist humans in several domains, from education to healthcare, from entertainment to the factory of the future. To find their place into our daily life, where complex interactions and collaborations with humans are expected, their social and physical interaction skills need to be further improved. The hallmark of humanoids is their anthropomorphic shape, which facilitates the interaction but at the same time increases the expectations of the human in terms of advanced cooperation capabilities. Cooperation with humans requires an appropriate modeling and real-time estimation of the human state and intention. This information is required both at a high level by the cooperative decision-making policy and at a low level by the interaction controller that implements the physical interaction. Real-time constraints induce simplified models that limit the decision capabilities of the robot during cooperation. In this article, we review the current achievements in the context of human-humanoid interaction and cooperation. We report on the cognitive and cooperation skills that the robot needs to help humans achieve their goals, and how these high-level skills translate into the robot’s low-level control commands. Finally, we report on the applications of humanoid robots as humans’ companions, co-workers, or avatars.

Humanoid Robot Application as COVID-19 Symptoms Checker Using Computer Vision and Multiple Sensors

Novel Corona Virus (nCoV) infects human’s respiratory system. It spreads easily when an infected person makes a close contact with other people. To prevent its massive spread, it is necessary to ensure anyone coming to a certain place is not being infected. The symptoms include high body temperature (≥37.5°C) and low oxygen saturation level (≤95%). This day, most places only check the human body temperature. Thus, the authors are interested to make an attempt to design a system that is able to measure both human body temperature and oxygen saturation level. This work also applies the 7-DoF Upper-Body of Humanoid Robot to prevent virus spread from and to the employee. The system will detect the coming of visitors by using face detection. It requires 7.24 seconds to detect the visitor without a mask, and 1.26 second when the visitor wears a mask. The body temperature measurement was done using GY-906 temperature sensor with an error of 0.51%. For the oxygen saturation level measurement, MAX30100 pulse oximeter module was applied and showed an error of 0.78%. In addition, the upper-body of humanoid robot will perform some gestures to instruct the visitors in every process of the system. The implemented 7-DoF upper-body of humanoid robot has 93.33% gesture comprehension rate. In conclusion, the overall system has been tested and showed success rate up to 75%.

Motion coordination for humanoid jumping using maximized joint power

Jumping capability of humanoid robots can be considered as one of the cruxes to improve the performance of future humanoid robot applications. This paper presents an optimization method on a three-linkage system to achieve a jumping behavior, which is followed by the clarification of the mathematical modeling and motor-joint model with practical factors considered. In consideration of the constraints of ZMP and the performance of the motor, the output power of the joint motors is maximized as much as possible to achieve a higher height. Finally, the optimization method is verified by the simulation and experiment. Different from other electric driven robots, which take the output power of the joint as the constraint, we maximize the output power of the joint to optimize the hopping performance of the robot. Realizing dynamic jumping of humanoid robots can also provide a solid foundation for further research on running, which can greatly enhance the environmental adaptability.

A Flexible Multi-Functional Smart Skin for Force, Touch Position, Proximity, and Humidity Sensing for Humanoid Robots

Artificial smart skins capable of interacting with people and sensing environmental stimuli have become a research topic in humanoid robotic applications. However, previously reported architectures suffer difficulties in achieving concurrent multi-dimensional sensing in a simple structure with low system costs. To address this issue, in this paper, an artificial smart skin constructed with polyimide/copper/polyvinylidene fluoride (PVDF) is presented for detecting 2D-position, proximity, dynamic force, and humidity via a smart combination of piezoelectric- and capacitive-effects. Moreover, a follow-up filtering algorithm is proposed to separate and calculate the stimuli associated with capacitance changes (position, proximity, and humidity). The proposed system achieves overall force and capacitive sensitivities of 0.05 N and 7 fF, a humidity responsivity at 0.22%/RH% over a relative humidity range of 10%–90% RH, a spatial resolution of 0.29 mm. This simple-structured device supports multiple functions with low system costs, thus advancing the field of robotics smart skins.

Use of Humanoid Robot in Dementia Care: A Literature Review

Dementia is a prevalent age-related disease that affects an individual’s quality of life. Cognitive decline is the most common symptom of dementia that consequently causes problems with memory, language, and apathy, communication, thinking ability, difficulty in problem-solving and doing their daily living activities independently. In recent years, researchers have tried to improve the quality of life of people living with dementia by utilizing new technologies such as robots. This study aims to investigate specifically the application of humanoid robots in refuting the risk of dementia by focusing on three approaches: 1) cognitive-communication improvement, 2) psychomotor therapy, and 3) music therapy. The results indicate that having humanoid robots as companions may serve as an effective therapy that helps people living with dementia (PLwD) with their cognitive function, motor skills, language, and communication skill. It also may decrease psychiatric symptoms by involving PLwD which will lead to improvement in their quality of life. The humanoid robots can also help reduce cognitive decline by helping PLwD perform exercises.

A Systematic Review for Service Humanoid Robotics Model in Hospitality

Nowadays, the Fourth Industrial Revolution has brought artificial intelligence to the forefront, and more and more intelligent robots begin to be used in the hospitality industry. In this study, the application of service humanoid robots in the hospitality industry is investigated based on Cardiff Metropolitan University EUREKA Robotics Lab’s robot as reported by Lab (in Eureka robotics lab, 2017, https://www.cardiffmet.ac.uk/technologies/Pages/EUREKA-Robotics-Lab.aspx). The research ontology of this study is post-positivism. The research philosophy of this research is phenomenology. Phenomenological studies have indicated that this phenomenon can only be truly understood and experienced through subjective immersive research directly involving researchers, and the interaction among researchers is an integral part of the research. In this study, the data are collated through case researches and experimental interviews. Finally, Some proposals for transforming the traditional hospitality industry into the direction of intelligence is summarized. In future research, a technical model combining artificial intelligence will be further developed.

Highly sensitive pressure sensor with broad linearity via constructing a hollow structure in polyaniline/polydimethylsiloxane composite

Flexible pressure sensors are increasingly required for their widely practical applications in health monitoring, humanoid robotics and wearable electronics. Although the geometric microstructure design or active material selection for sensor has been manipulated by many researchers, achieving the desired pressure sensor possessing high sensitivity over a broad linear detection range is still challenging. Herein, a flexible and wearable pressure sensor is demonstrated based on the polyaniline/polydimethylsiloxane (PANI/PDMS) composite with hollow structure and micro-protrude surface structure. The sensitivity and linearity of the as-fabricated sensor could be greatly enhanced through the construction of hollow structure and micro-protrude surface structure, reaching a sensitivity of 0.641 kPa−1 over a broad linear range (0.05–60 kPa), and the sensor also exhibits stable cycling performances (6000 cycles), fast response time (200 ms) and recovery time (150 ms). Importantly, the sensing mechanism of this sensor is theoretically studied, a sensing model based on tunneling effect and contact mechanic is proposed and its validity is experimentally verified. Finally, the pressure sensor demonstrates practical applications in object operations, answering mouse click and feet movements, thereby providing a significant guidance for constructing advanced electronic devices.

Effects of Teleoperated Humanoid Robot Application in Older Adults with Neurocognitive Disorders in Taiwan: A Report of Three Cases

Effects of Teleoperated Humanoid Robot Application in Older Adults with Neurocognitive Disorders in Taiwan: A Report of Three Cases

A Force and Temperature Sensor Array Based on 3-D Field-Coupled Thin-Film Transistors for Tactile Intelligence

Tactile sensors that acquire force and temperature information are key to machine tactile intelligence. In this article, an active tactile sensor incorporating an array of 3-D field-coupled thin-film transistors (FCTFTs) with a $4 \times 4$ pixelated polyvinylidene fluoride (PVDF)-based force and temperature sensors is studied. In order to enhance sensitivity and reduce power consumption, a 3-D FIN-shaped FCTFT is designed and a subthreshold operation is implemented. We have demonstrated its functions in human–machine interfacing, object characterization and recognition, force and temperature mapping, and dynamic force tracing. Such a tactile sensor array is promising for applications in machine tactile intelligence and humanoid robotics.

A facile and cost-effective approach to fabrication of high performance pressure sensor based on graphene-textile network structure

High performance flexible pressure sensors have received tremendous attention due to the potential applications in wearable electronics and humanoid robotics. Herein, a low-cost, time-saving fabrication strategy is reported to efficiently construct highly sensitive and scalable pressure sensors based on graphene-textile. The flexible pressure sensor was prepared through a dip coating approach where the graphene ink was used as the active material and textile with ordered network structure, serves as the flexible support matrix. By increasing the number of layers of the textile, the pressure sensor could achieve a high linear sensitivity value of 0.23 kPa−1, a broad pressure range from 0 to 140 kPa, and a durability over 800 cycles. It was found that the network structure of the graphene-textile contributed to the enhancement of the sensing performance due to the piezoresistive effect resulting from the deformation of conductive graphene-textile. Moreover, by virtue of its exceptional properties, it is demonstrate that the high performance flexible pressure sensor could be further used to detect human physiological signals, such as wrist pulse, finger press detection and walking state monitoring, indicating its promising potential to flexible and wearable electronics.

Multifunctional and highly sensitive piezoresistive sensing textile based on a hierarchical architecture

Flexible sensing materials have attracted tremendous attention for the practical applications in humanoid robotics and wearable electronics. However, achieving flexible sensors possessing high sensitivity and multifunctionality via a facile and robust manufacturing strategy is still challenging. Herein, a scalable and efficient fabrication strategy is employed to yield conductive textile with a hierarchical architecture as high performance piezoresistive sensing element, by assembling reduced graphene oxide and polyaniline nanorod arrays onto fabric fibers in sequence (PANI/rGO/textile). The pressure sensor, which is prepared by multilayer PANI/rGO/textile, exhibits ultrahigh sensitivity (97.28 kPa−1) and linear response over a wide pressure regime (0.0005–40 kPa), excellent durability (11000 cycles), wide working bandwidth (1–10 Hz), fast response time (≈30 ms) and recovery time (≈25 ms), and low detection limit (0.5 Pa). In practical applications, the pressure sensors are used to detect various human motions. Additionally, pressure sensor arrays could successfully perceive the magnitude and spatial distribution of diverse pressure stimuli. Moreover, the PANI/rGO/textile can be used for strain sensor directly, confirming a negative resistance variation and anisotropic strain response behavior. The strain sensor exhibits a high negative sensitivity (−78) and excellent durability (1000 cycles), which could be woven on clothing for human activities monitoring, thereby marking a significant progress for constructing high-performance wearable electronics.