Perceived Potential of Humanoid Robots

Background Humanoid robots with artificial intelligence have been implemented in many healthcare facilities including hospitals, nursing homes, and many others. Due to the development of technology and the increasing use of humanoid robots, it is expected that more advanced humanoid robots will be developed and implemented in healthcare facilities for better healthcare services. Based on this anticipation, this study proactively examined the public trust in humanoid AI robot (HAIR) doctors that we might have in the near future. Methods This study employed two scales that have been predominantly used to measure patient-doctor trust through an extensive search across different scholarships. For data collection, online surveys were administered by posting a weblink to the online survey through social media, mostly Facebook, Twitter, and KakaoTalk, in South Korea. Results Data analysis of 424 valid surveys found that the level of public trust in HAIR doctors as primary doctors was slightly higher than human doctors. For the data analysis using demographic variables, a series of t-test and ANOVA revealed that males showed a higher trust in HAIR doctors than females, while maintaining indifference in other demographic variables. Conclusion Based on the rapid development of AI and robot technology, the implementation of HAIR doctors for our healthcare service would be a reality in the near future as the public also becomes more familiar with interacting with humanoid robots. Therefore, a proactive preparation for the future is urgently needed for effective use of future technology as well as patients’ satisfaction.

International audience

Humanoid robots can imitate human behaviour and provide interactive services to humans due to their humanoid form, especially humanoid wheeled robots that can perform more complex tasks with the additional mobility. With the development of robotics technology, humanoid robots have been used increasingly in the domestic environment where the robot needs to interact with unknown environments. This requires the robot to have both the ability to track with high accuracy and the ability to comply with complex environments. It is known that the robots with impedance control can have a superior performance in terms of compliance with unknown contact environments. However, the mobility of humanoid robots with wheels complicates the dynamic model of robots, which makes the development of impedance control challenging. In this letter, a whole-body impedance control approach for humanoid wheeled robots is proposed, with fuzzy adaptive systems to compensate for the uncertain dynamics of the controlled system. This approach realizes safe interaction and compliant operation with unknown environments including humans. Additionally, the experimental results conducted on a humanoid wheeled robot illustrate the effectiveness of the proposed controller.

(2004). Robo-Erectus: a low-cost autonomous humanoid soccer robot. Advanced Robotics: Vol. 18, No. 7, pp. 717-720.

Problem statement: Present researches focus to make humanoid robots more and more autonomous so they can assist human in daily works like taking care of children, aged or disabled persons. In such social activities, the contemporar y humanoid robots are expected to have human like morphology and gait. Studies on bipedal locomotion for humanoid robots are then part of the hottest topics in the field of robotic researches. Knowing the benefits of arm swinging for human gait, we propose in this study a new prototype of female humanoid robot morphology having the capabilities to swing arms during step walking. Approach: A new humanoid robot prototype had been introduced based on a human morphology corresponding to a woman whose weight is 70 kg and height is 1,73 m and using realistic gait parameters of a women. The female hu manoid robot prototype was composed of fifteen links associated to twenty-six degrees of freedom. Winter statistical model had been applied to determ ine all physical parameters corresponding to each link. Modeling the proposed humanoid robot implies first to establish the kinematic model basically founded on Euler's transformation matrix and then to set th e dynamic model computed using the Newton-Euler method. To show how the arms played an important role in bipedal gait, we had chosen to consider the whole body as two independent robotic systems: the upper body and the lower body. Results: Both three dimensional kinematic and dynamic models of the humanoid robot had been developed. The three dimensional humanoid robot was controlled via a feedback linearization control during the single su pport, impact and double support phases. The simulation results showed the arm swing during the step of walking. Conclusion: The humanoid robot proposed has a human like morphology and ensures the function of a step walking with arm swinging. The applied control laws have ensured to the robot desired performances during a step walking.

A humanoid robot is developed as a platform for the research on perception-action coupling in intelligent behaviour of humanoid type robots. The H6 has the features as follows: 1) a body which has enough DOFs and each joint has enough torque for full body motion, 2) a PC/AT compatible on-board computer which is controlled by RT-linux so that low-level to high-level control is achieved simultaneously, 3) is self-contained and connected to a network via radio ethernet, 4) a 3D vision function can be applied. The H6 is expected to be a common test-bed for experiment and discussion for various aspects of intelligent humanoid robotics.

Gestures and speech modalities play potent roles in social learning, especially in educational settings. Enabling artificial learning companions (i.e., humanoid robots) to perform human-like gestures and speech will facilitate interactive social learning in classrooms. In this paper, we present the implementation of human-generated gestures and speech on the Pepper robot to build a robotic teacher. To this end, we transferred a human teacher gesture to a humanoid robot using a web and a kinect cameras and applied a video-based markerless motion capture technology and an observation-based motion mirroring method. To evaluate the retargeting methods, we presented different types of a humanoid robotic teacher to six teachers and collect their impressions on the practical usage of a robotic teacher in the classroom. Our results show that the presented AI-based open-source gesture retargeting technology was found attractive, as it gives the teachers an agency to design and employ the Pepper robot in their classes. Future work entails the evaluation of our solution to the stakeholders (i.e. teachers) for its usability.KeywordsMotion retargetingTeacher robotNon-verbal behaviorMotivationPepper robot

This paper describes the design of an integrated system for humanoid robotics that consists of three key components, 3D vision, motion planning and bipedal control. Layered system design is adopted to achieve concurrency as well as small latency. Implementation using our humanoid type robot H7 and experiments with this architecture are described. The H7 is expected to be a common test-bed in experiments and discussion for various aspects of intelligent humanoid robotics.

Even if a robot is not designed with a specific impression, if there is a means that can add an impression later to the robot, it will be useful for social robot design, we considered. In particular, anthropomorphism seems to be an important impression of designing social interaction between humans and robots. In the movie, ”STAR WARS,” there is a non-humanoid robot, called R2-D2, which communicates mainly by sounds. A humanoid interpreter robot, called C-3PO, responds to the sound of R2-D2 with natural language and gesture. And the audience finds the personality in R2-D2 richer than the personality which is based on the information which R2-D2’s sounds have. It might be possible to change the impression of a non-humanoid robot emitting simple sounds by communication with a humanoid robot that speaks a natural language and make gestures. We conducted an impression evaluation experiment. In the condition where robots are interacting, the observer evaluated anthropomorphism of the nonhumanoid robot more than in the non-interacting condition. There were also some other impressions that have changed.

Cost Oriented Humanoid Robots

To accelerate the deep application of deep learning in text data processing, an English statistical translation system is established and applied to the question answering of humanoid robot. Firstly, the model of machine translation based on recursive neural network is implemented. A crawler system is established to collect English movie subtitle data. On this basis, an English subtitle translation system is designed. Then, combined with sentence embedding technology, the Particle Swarm Optimization (PSO) algorithm of meta-heuristic algorithm is adopted to locate the defects of translation software. A translation robot automatic question and answer interactive module is constructed. Additionally, the hybrid recommendation mechanism based on personalized learning is built using blockchain technology. Finally, the performance of translation model and software defect location model is evaluated. The results show that the Recurrent Neural Network (RNN) embedding algorithm has certain effect of word clustering. RNN embedded model has a strong ability to process short sentences. The strongest translated sentences are between 11 and 39 words long, while the weakest translated sentences are between 71 and 79 words long. Therefore, the model must strengthen the processing of long sentences, especially character—level input. The average sentence length is much longer than word-level input. The model based on PSO algorithm shows good accuracy in different data sets. This model averages better performance on Tomcat, standard widget toolkits, and Java development tool datasets than other comparison methods. The average reciprocal rank and average accuracy of the weight combination of PSO algorithm are very high. Moreover, this method is greatly affected by the dimension of the word embedding model, and the 300-dimension word embedding model has the best effect. To sum up, this study proposes a good statistical translation model for humanoid robot English translation, which lays the foundation for intelligent interaction between humanoid robots.

Teaching human motion to a humanoid social robot is important because it enables a humanoid social robot to interact with humans more naturally and in a friendly manner. Recently, a depth camera-based human motion teaching has been developed. However, inverse kinematic analysis using human motion skeletal data obtained from the depth camera is not general but rather robot structure-dependent. Thus, in this paper, we present a more general approach to compute joint angles from the skeletal data obtained from a depth camera using a recursive inverse kinematic algorithm. With a known base body orientation, each joint angle is recursively computed from the base body (torso) to the tree end body (robot hand). To validate the proposed recursive inverse kinematic algorithm, simulations of a humanoid robot model have been carried out using the RecurDyn multibody analysis software. The virtual humanoid robot consists of two 6 DOF arms and a 2DOF waist. The human upper body motion when walking has been captured using a Microsoft Azure Kinect depth camera. The hand motion from the depth camera and that from the simulation have been compared to investigate the effectiveness of the proposed algorithm.

The main objectives of the present work are to model and implement a control system of five degrees of freedom (5 DOF) humanoid arm by using an exoskeleton system with 3 DOF. The exoskeleton system is used to transport the movements of the human’s arm to the controller to control the humanoid arm by using sensors at each target joint to measure the angular displacement of it. To achieve this target, a kinematic analysis of the 5 DOF arm robot has been carried out including the forward, and solving the inverse kinematics. In addition, heterogeneous teleoperation based on forward and inverse kinematic between the humanoid arm and the exoskeleton model has been performed. Also, an experimental set up has been arranged to include the sensors considered (angular displacement sensors), control unit, signal-processing boards, and the actuators (servo motors of the humanoid arm robots). The control experiments have been conducted based on PID control. Keywords : Forward kinematic, inverse kinematic, teleoperation, humanoid robot Cite this Article Elsamanty M, Sayed M, Abdr Aboo S. Heterogeneous Teleoperation Model for Controlling 3D Printed Humanoid Robot Arm with 5 DOF using 3 DOF Exoskeleton. Journal of Control & Instrumentation. 2019; 10(2): 1–15p.

A humanoid robot is a robot that has a similar appearance with humans. Although appearance is the one of the important features of humanoid robots, human-like behaviors and task solving abilities are more meaningful features in daily life. To make humanoid robots more useful, they should have the capacity to learn new abilities. However, today’s humanoid robots are not smart enough to adapt to their working environments. In this paper, we propose a method to develop new abilities of humanoid robots on the basis of imitation, one of the most powerful methods to learn a new skill, not only for humans but also for humanoid robots. To achieve this goal, we designed and implemented a wearable interface to teach humanoid robots via user demonstration. Magnetic markers and flex sensors are applied for capturing human motion. A head mount display and a microphone are used for communicating with the partner robot. A vision channel and speech channel are employed to communicate with the partner robot. The wearable system assists the user and enhances interaction with the robot through an intuitive motion imitating method and multimodal communication channels via which commands are given and sensory feedback is received. A vision channel is used to complement the weakness in recognizing surrounding states. A human teacher can sense the environment by sharing the robot’s sight using the head mount display and he or she can decide the most appropriate behavior for the observed situation. When the teacher concludes that there is no proper behavior among the robot’s abilities, a new ability can be trained through demonstration by the teacher. We conducted a kinematic analysis on both a human user and a partner robot to overcome the joint difference problem when transferring motion from the human user to the robot. We used the humanoid robot AMIO as a test bed to validate the wearable interface and found that we could make the robot more intelligent with the wearable interface.

In the near future, humanoid robots will act as the partners of human beings in daily life. Among numerous human-like competencies, motion of humanoid robots is critical for providing humans with richer interactions with such robots. Motion plays an essential role in complementing spoken communication. Moreover, the motions of humanoid robots generate nonverbal communication in various contexts. Through this nonverbal communication, humans can interact with robots not only directly but also indirectly or even unconsciously, as if the robot were simply part of the environment. Before the developments of humanoid robots, embodied conversational agents (ECAs) were introduced as virtual embodied representations of humans that communicated multi-modally with humans and there has been a great deal of research on ECA behavior. ECAs and humanoid robots share many features in terms of how they communicate with humans. Nevertheless, simply adapting knowledge gathered from current ECA studies to a humanoid robot study is insufficient for the following reasons: 1. ECA studies lack knowledge focused on nonverbal communication, which has become more important in the physical world; 2. ECA studies have focused on developing agent-centered intelligence rather than a user- centered experience; 3. ECA studies have developed logics to generate motions automatically rather than to provide designers with the practical knowledge necessary to design desirable motions. Motivated by these three arguments, we seek to pioneer a new field of motion design between robot engineering and design discipline. To bring this motion study into design discipline, we focused on human-centered experience through nonverbal communication with a humanoid robot. This paper aims to outline sharable user experience in order to help designer create desirable motions for humanoid robots in various speechless contexts.