Personal Robots Research Articles

Personal Assistant Robot

Since the boom in science and technology, humans have been trying to invent machines that could reduce their efforts in day to day activities. In this paper, we develop a personal assistant robot that could pick up objects and return it to the user. The robot is controlled using an android application in mobile phones. The robot can listen to user’s command and then respond in the best way possible. The user can command the robot to move to given location, capture images and pick objects. The robot is equipped with ultrasonic sensor and web camera that helps it to move to different location effectively. It is also equipped with sleds that play important role in object picking process. The robot uses a tiny YOLOv3 model which is rigorously trained on several images of the object. There are some possible improvements that can be achieved which could help this robot to be used in several other fields as well.

Positive Turn in Elder-Care Workers’ Views Toward Telecare Robots

Robots have been slowly but steadily introduced to welfare sectors. Our previous observations based on a large-scale survey study on Finnish elder-care workers in 2016 showed that while robots were perceived to be useful in certain telecare tasks, using robots may also prove to be incompatible with the care workers’ personal values. The current study presents the second wave of the survey data from 2020, with the same respondents (N = 190), and shows how these views have changed for the positive, including higher expectations of telecare robotization and decreased concerns over care robots’ compatibility with personal values. In a longitudinal analysis (Phase 1), the positive change in views toward telecare robots was found to be influenced by the care robots’ higher value compatibility. In an additional cross-sectional analysis (Phase 2), focusing on the factors underlying personal values, care robots’ value compatibility was associated with social norms toward care robots, the threat of technological unemployment, and COVID-19 stress. The significance of social norms in robot acceptance came down to more universal ethical standards of care work rather than shared norms in the workplace. COVID-19 stress did not explain the temporal changes in views about robot use in care but had a role in assessments of the compatibility between personal values and care robot use. In conclusion, for care workers to see potential in care robots, the new technology must support ethical standards of care work, such as respectfulness, compassion, and trustworthiness of the nurse–patient interaction. In robotizing care work, personal values are significant predictors of the task values.

Applicability of the GDPR on Personal Household Robots

Applicability of the GDPR on Personal Household Robots

On the Safety of Mobile Robots Serving in Public Spaces

Since 2014, a specific standard has been dedicated for the safety certification of personal care robots, which operate in close proximity to humans. These robots serve as information providers, object transporters, personal mobility carriers, and security patrollers. In this article, we point out the shortcomings concerning EN ISO 13482:2014, which encompasses guidelines regarding the safety and design of personal care robots. In particular, we argue that the current standard is not suitable for guaranteeing people's safety when these robots operate in public spaces. Specifically, the standard lacks requirements to protect pedestrians and bystanders. The guideline implicitly assumes that private spaces, such as households and offices, present the same hazards as in public spaces. We highlight the existence of at least three properties pertaining to robots’ use in public spaces. These properties include (1) crowds, (2) social norms and proxemics rules, and (3) people's misbehaviours. We discuss how these properties impact robots’ safety. This article aims to raise stakeholders’ awareness on individuals’ safety when robots are deployed in public spaces. This could be achieved by integrating the gaps present in EN ISO 13482:2014 or by creating a new dedicated standard.

APRIL: Personal Robots at Your Service.

APRIL: Personal Robots at Your Service.

A Study of Optimized EEG Signal Induction/Extraction Techniques for Basic Motion Control of Personal Robots for Physically Impaired Users

When interfaces utilizing EEG signals are used, these signals can be induced through diverse association techniques. In the present article, differences in recognition performance of the systems related to robot control techniques according to diverse association techniques have been analyzed. For this purpose, elements that can affect the performance other than association techniques were excluded as much as possible, and the focus was placed on the performance analysis per association technique. According to the study results of the present article, the movement association technique based on gestures showed the highest recognition performance in the robot control system for multiple users. In the robot control system for single users, hearing-based phonation association is considered to show the highest recognition performance. In the study results of the present article, superior recognition performance is considered to be derived than the recognition performance displayed by existing systems when applied to the robot control area utilizing EEG signals.

Comparison between Recurrent Networks and Temporal Convolutional Networks Approaches for Skeleton-Based Action Recognition.

Action recognition plays an important role in various applications such as video monitoring, automatic video indexing, crowd analysis, human-machine interaction, smart homes and personal assistive robotics. In this paper, we propose improvements to some methods for human action recognition from videos that work with data represented in the form of skeleton poses. These methods are based on the most widely used techniques for this problem—Graph Convolutional Networks (GCNs), Temporal Convolutional Networks (TCNs) and Recurrent Neural Networks (RNNs). Initially, the paper explores and compares different ways to extract the most relevant spatial and temporal characteristics for a sequence of frames describing an action. Based on this comparative analysis, we show how a TCN type unit can be extended to work even on the characteristics extracted from the spatial domain. To validate our approach, we test it against a benchmark often used for human action recognition problems and we show that our solution obtains comparable results to the state-of-the-art, but with a significant increase in the inference speed.

Body Language for Personal Robot Arm Assistant

This article presents an exploratory study aimed at: (i) understanding participants’ first impression of the Cyton Gamma 1500, a small machine-like robot arm, and (ii) designing robot body language to convey certain intentions with regard to a personal assistant robotic application. The between-group study comprised of three distinct groups of participants. Each group had a different first encounter with the robot arm: the first group saw an idly sitting robot arm; the second group watched another person working with the robot; lastly, the third group worked with the robot themselves. They rated the robot arm on a bipolar adjective questionnaire after the first encounter which gives us insights into participant’s “first impression”. Then they performed a categorization task where they chose the most suitable posture for conveying specific messages. The objective here was to select postures that can easily convey the robot assistant’s intentions to users in future. The two main findings of the study are: (1) participants’ impression of the robot arm does not differ significantly across the three groups despite having different “first encounter” with the robot, and (2) certain postures are easily relatable to the message they convey (like, Robot is saying “Hi!”), while certain others are not (like, Robot has surrendered). In light of phenomenological theories of communication, it was concluded that tempered forms of anthropomorphic or zoomorphic postures are more easily identified than completely abstract postures. The findings of this study can be used to design robot-specific body language for robot arms.

Human vital sign determination using tactile sensing and fuzzy triage system

The ability to quickly and accurately triage a person’s medical condition in an emergency situation or other critical scenarios could mean the difference between life and death. Endowing a robotic system with vision and tactile capabilities, similar to those of medical professionals, and thus enabling robots to assess a patient’s status in an emergency is a highly sought after characteristic in healthcare robotics. This paper presents a novel fuzzy triage system exploiting visual and tactile sensing, to equip a robot with the skills to accurately determine key vital signs in humans. There are three key signs of human health: respiratory rate, pulse rate (Beats Per Minute (BPM)) and capillary refill time. Using ground truth from a medical professional, the fuzzy triage system is trained and validated initially with informed synthetic data and then further evaluated using vital signs data collected from subjects in a pilot study. Results from this pilot study indicate that the fuzzy triage system is capable of classifying a patient’s health using the novel approaches for collecting BPM, Respiratory Rate (RR) and Capillary Refill Time (CRT) which replicate, to some extent, the approaches used by medical professionals for measuring vital signs. Furthermore, the intelligent system proved capable of determining whether a pulse was regular or arrhythmic, whether respiratory rate was regular or irregular, and determining the subject’s capillary refill time. Such results imply that this system could ultimately be used, for example, in a home assistance robot for elderly or disabled persons, or as a first responder robot. Ultimately the aim would be that these methods could be utilised by robotic systems in emergency scenarios or disaster zones.

“Siri, Show Me Scary Images of AI”: Effects of Text-Based Frames and Visuals on Support for Artificial Intelligence

This research note examines how framing influences attitudes toward artificial intelligence (AI). It uses an experiment embedded in a nationally representative online survey to test the effects of text-based frames and visuals on opinion about developing, funding, and banning AI. Participants exposed to a “social progress” frame reported greater support for AI than those exposed to a “Pandora’s box” frame. Images (virtual assistants, personal robots, menacing movie AIs, or none) did not influence opinion by themselves but interacted with textual frames to do so. The results extend our understanding of framing effects on public attitudes toward emerging technologies.

P-Rob Six-Degree-of-Freedom Robot Manipulator Dynamics Modeling and Anti-Disturbance Control

In this paper, the problem of modeling and anti-disturbance control is studied for lightweight personal robotics (P-Robs) with a six-degree-of-freedom robot manipulator to solve the movement instability phenomenon caused by time-varying uncertain disturbances during the movement of the robot manipulator. The detailed dynamical equations of the P-Rob system are solved based on the Lagrange energy equation, and the actual dynamical model of the robot manipulator system is obtained. The disturbance observer is designed to estimate the disturbance effectively, and an integral sliding mode control algorithm is proposed to realize tracking control. Stability analysis of the system is carried out using the Lyapunov function. Finally, experiments are conducted on an actual P-Rob system model, and the experimental results show that the robot manipulator system tracks the desired trajectory effectively, which validates the effectiveness of the proposed control algorithm.

Should We Treat Teddy Bear 2.0 as a Kantian Dog? Four Arguments for the Indirect Moral Standing of Personal Social Robots, with Implications for Thinking About Animals and Humans

The use of autonomous and intelligent personal social robots raises questions concerning their moral standing. Moving away from the discussion about direct moral standing and exploring the normative implications of a relational approach to moral standing, this paper offers four arguments that justify giving indirect moral standing to robots under specific conditions based on some of the ways humans—as social, feeling, playing, and doubting beings—relate to them. The analogy of “the Kantian dog” is used to assist reasoning about this. The paper also discusses the implications of this approach for thinking about the moral standing of animals and humans, showing why, when, and how an indirect approach can also be helpful in these fields, and using Levinas and Dewey as sources of inspiration to discuss some challenges raised by this approach.

Experiencing autonomous futures: Engaged learning with next generation technology

Digital software has been proliferating in the classroom, frequently replacing students’ hands on experiences. This article reports on a study that tested how hands on experiences with physical emerging technology, namely personal robots, drones, cameras, and echo dots, may improve or impair student learning and enhance or diminish the classroom experience. This study examines the potential impact of hands on experiences on student knowledge, skills, and values regarding emerging technology in the context of a course that employed traditional learning, defined as theoretical applications of next generation technology, namely autonomous vehicles during the first half, and hands on experiences with physical emerging technologies related to domotics, during the second half. Using three diagnostics, tweets, reflections, and discussion posts, we suggest that hands on experiences allowed students to more easily identify potential challenges with, and reduced their fears regarding, emerging technology. Additionally, our findings suggest that traditional learning methods may decrease familiarity with most technologies, whereas hands on experiences increased familiarity. Hands on experiences also appear to reverse several other trends associated with traditional learning. Ultimately, given the proliferation of technologies in the modern world and the impacts of automation, hands on experiences may be even more valuable than expected to students as they enter the workforce.

Rapid Development of a Mobile Robot for the Nakanoshima Challenge Using a Robot for Intelligent Environments

Automated mobile platforms are commonly used to provide services for people in an intelligent environment. Data on the physical position of personal electronic devices or mobile robots are important for information services and robotic applications. Therefore, automated mobile robots are required to reconstruct location data in surveillance tasks. This paper describes the development of an autonomous mobile robot to achieve tasks in intelligent environments. In particular, the robot constructed route maps in outdoor environments using laser imaging detection and ranging (LiDAR), and RGB-D sensors via simultaneous localization and mapping. The mobile robot system was developed based on a robot operating system (ROS), reusing existing software. The robot participated in the Nakanoshima Challenge, which is an experimental demonstration test of mobile robots in Osaka, Japan. The results of the experiments and outdoor field tests demonstrate the feasibility of the proposed robot system.

Toward privacy-sensitive human–robot interaction: Privacy terms and human–data interaction in the personal robot era

Abstract Can we have personal robots without giving away personal data? Besides, what is the role of a robots Privacy Policy in that question? This work explores for the first time privacy in the context of consumer robotics through the lens of information communicated to users through Privacy Policies and Terms and Conditions. Privacy, personal and non-personal data are discussed under the light of the human–robot relationship, while we attempt to draw connections to dimensions related to personalization, trust, and transparency. We introduce a novel methodology to assess how the “Organization for Economic Cooperation and Development Guidelines Governing the Protection of Privacy and Trans-Border Flows of Personal Data” are reflected upon the publicly available Privacy Policies and Terms and Conditions in the consumer robotics field. We draw comparisons between the ways eight consumer robotic companies approach privacy principles. Current findings demonstrate significant deviations in the structure and context of privacy terms. Some practical dimensions in terms of improving the context and the format of privacy terms are discussed. The ultimate goal of this work is to raise awareness regarding the various privacy strategies used by robot companies while ultimately creating a usable way to make this information more relevant and accessible to users.

What’s in the Box: Design of an Open Didactic Robot Environment

We present a realization of a didactic robot environment for robot PUMA 560 for educational and research purposes. Robot PUMA 560 is probably the mathematically best-described robot, and therefore it is frequently used for research and educational purposes. A developed control environment consists of a robot controller and teach pendant. The advantage of using a personally developed solution is its open structure, which allows various tests and measurements to be performed, and that is highly convenient for educational and research purposes. The motivation behind the design of this personal didactic robot control environment arose from a survey for students after the first Summer School on Mechatronic Systems. The student questionnaire revealed severe discrepancies between theory and practice in education. Even though the primary purpose of the new control environment for robot PUMA 560 was research, it was established that it is a viable lab resource that allows for the connection between theoretical and industrial robotics. It was used for the duration of four Summer Schools and university courses. Since then, it has been fully integrated into International Burch University’s Electrical and Electronics Engineering curriculum through several courses on the bachelor and master levels for multidisciplinary problem-based learning (PBL) projects.

Human-Like Arm Motion Generation: A Review

In the last decade, the objectives outlined by the needs of personal robotics have led to the rise of new biologically-inspired techniques for arm motion planning. This paper presents a literature review of the most recent research on the generation of human-like arm movements in humanoid and manipulation robotic systems. Search methods and inclusion criteria are described. The studies are analyzed taking into consideration the sources of publication, the experimental settings, the type of movements, the technical approach, and the human motor principles that have been used to inspire and assess human-likeness. Results show that there is a strong focus on the generation of single-arm reaching movements and biomimetic-based methods. However, there has been poor attention to manipulation, obstacle-avoidance mechanisms, and dual-arm motion generation. For these reasons, human-like arm motion generation may not fully respect human behavioral and neurological key features and may result restricted to specific tasks of human-robot interaction. Limitations and challenges are discussed to provide meaningful directions for future investigations.

Facile Approach to Fabricating Stretchable Organic Transistors with Laser-Patterned Ag Nanowire Electrodes.

Stretchable electronics are poised to revolutionize personal healthcare and robotics, where they enable distributed and conformal sensors. Transistors are fundamental building blocks of electronics, and there is a need to produce stretchable transistors using low-cost and scalable fabrication techniques. Here, we introduce a facile fabrication approach using laser patterning and transfer printing to achieve high-performance, solution-processed intrinsically stretchable organic thin-film transistors (OTFTs). The device consists of Ag nanowire (NW) electrodes, where the source and drain electrodes are patterned using laser ablation. The Ag NWs are then partially embedded in a poly(dimethylsiloxane) (PDMS) matrix. The electrodes are combined with a PDMS dielectric and polymer semiconductor, where the layers are individually transfer printed to complete the OTFT. Two polymer semiconductors, DPP-DTT and DPP-4T, are considered and show stable operation under the cyclic strain of 20 and 40%, respectively. The OTFTs maintain electrical performance by adopting a buckled structure after the first stretch-release cycle. The conformability and stretchability of the OTFT is also demonstrated by operating the transistor while adhered to a finger being flexed. The ability to pattern highly conductive Ag NW networks using laser ablation to pattern electrodes as well as interconnects provides a simple strategy to produce complex stretchable OTFT-based circuits.

Coaxiality Evaluation of Coaxial Imaging System with Concentric Silicon-Glass Hybrid Lens for Thermal and Color Imaging.

Thermal imaging is useful for tasks such as detecting the presence of humans and recognizing surrounding objects in the operation of several types of robots, including service robots and personal mobility robots, which assist humans. Because the number of pixels on a thermal imager is generally smaller than that on a color imager, thermal images are more useful when combined with color images, assuming that the correspondence between points in the images captured by the two sensors is known. In the literature, several types of coaxial imaging systems have been reported that can capture thermal and color images, simultaneously, from the same point of view with the same optical axis. Among them, a coaxial imaging system using a concentric silicon–glass hybrid lens was devised. Long-wavelength infrared and visible light was focused using the hybrid lens. The focused light was subsequently split using a silicon plate. Separate thermal and color images were then captured using thermal and color imagers, respectively. However, a coaxiality evaluation of the hybrid lens has not been shown. This report proposes an implementation and coaxiality evaluation for a compact coaxial imaging system incorporating the hybrid lens. The coaxiality of the system was experimentally demonstrated by estimating the intrinsic and extrinsic parameters of the thermal and color imagers and performing 2D mapping between the thermal images and color images.

Human interaction behavior modeling using Generative Adversarial Networks

Recently, considerable research has focused on personal assistant robots, and robots capable of rich human-like communication are expected. Among humans, non-verbal elements contribute to effective and dynamic communication. However, people use a wide range of diverse gestures, and a robot capable of expressing various human gestures has not been realized. In this study, we address human behavior modeling during interaction using a deep generative model. In the proposed method, to consider interaction motion, three factors, i.e., interaction intensity, time evolution, and time resolution, are embedded in the network structure. Subjective evaluation results suggest that the proposed method can generate high-quality human motions.