Several Types Of Robots Research Articles

HiroPoseEstimation: A Dataset of Pose Estimation for Kid-Size Humanoid Robot

Pose estimation is a field of computer vision research that involves detecting, associating, and tracking data points on body parts. It is used for health monitoring, sign language understanding, human gesture control, elderly activities, sports, and humanoid robot pose estimation. The anatomy of a humanoid robot is similar to a human, which forms the basis for utilizing humanoid robot pose estimation. The Humanoid League is a major domain of the RoboCup competition, featuring soccer matches between humanoid robots. Pose estimation is used to measure the robot’s performance. Nevertheless, there have not been many research done on this subject. A new dataset model needs to be developed to solve the proposed problem. This work introduces HiroPoseEstimation, a kid-size humanoid robot dataset with several types of robots used in various poses based on movements in a soccer game. It is evaluated with both bottomup and top-down approaches using keypoint mask R-CNN and single-stage encoder-decoder model. Both methods demonstrate good performance on the proposed dataset.

Keeping an Eye on Earth’s Oceans With Argo Robots

Have you ever wondered how scientists know what is happening deep below the surface of the ocean? There are several types of robots that can dive below the sea surface and bring back data from underwater. One type of robot, called an Argo float, moves through the middle depths of the ocean with the currents and comes to the surface once every 10 days, to tell scientists about the information that it has collected. Currently, there are about 4,000 Argo robots keeping an eye on Earth’s oceans every day. These robots measure ocean temperature and saltiness, and some can also monitor more complex chemical and biological parameters. Argo robots provide another tool in an oceanographer’s toolbox, to help scientists understand how the ocean works and how it impacts not only marine life, but also the whole Earth.

A Novel Ant Colony-inspired Coverage Path Planning for Internet of Drones

Coverage Path Planning (CPP) is a fundamental problem widely used in various applications such as monitoring, patrol, mapping, and sweeping. Several types of robots can perform CPP, which has become very popular with the use of multiple drones. The Internet of Drones (IoD) is an emerging technology that aims to facilitate a multi-drone environment for various applications. In this context, coordination and organization of drones are crucial to avoid collisions and congestion in the airspace. One way to achieve this is by using well-defined airways. CPP tasks are often performed using multiple drones to cover a given area, which can be integrated into the IoD system. However, existing CPP solutions for drones do not fully consider collaboration capabilities between them, specific energy constraints, and the dynamic IoD scenario. To address these challenges, this work proposes an Ant Colony Optimization Algorithm for CPP in IoD (AntIoD), considering energy consumption. This scenario is particularly challenging due to the unique characteristics of being a mix of CPP for terrestrial vehicles with road constraints and CPP for drone networks. We compared our approach, AntIoD, with three recent solutions from the literature. The results reveal that AntIoD outperformed them in all simulated scenarios by at least 10% in terms of energy efficiency when compared to the best scenarios of the other algorithms.

Scalability of Cyber-Physical Systems with Real and Virtual Robots in ROS 2.

Nowadays, cyber-physical systems (CPSs) are composed of more and more agents and the demand for designers to develop ever larger multi-agent systems is a fact. When the number of agents increases, several challenges related to control or communication problems arise due to the lack of scalability of existing solutions. It is important to develop tools that allow control strategies evaluation of large-scale systems. In this paper, it is considered that a CPS is a heterogeneous robot multi-agent system that cooperatively performs a formation task through a wireless network. The goal of this research is to evaluate the system's performance when the number of agents increases. To this end, two different frameworks developed with the open-source tools Gazebo and Webots are used. These frameworks enable combining both real and virtual agents in a realistic scenario allowing scalability experiences. They also reduce the costs required when a significant number of robots operate in a real environment, as experiences can be conducted with a few real robots and a higher number of virtual robots by mimicking the real ones. Currently, the frameworks include several types of robots, such as the aerial robot Crazyflie 2.1 and differential mobile robots Khepera IV used in this work. To illustrate the usage and performance of the frameworks, an event-based control strategy for rigid formations varying the number of agents is analyzed. The agents should achieve a formation defined by a set of desired Euclidean distances to their neighbors. To compare the scalability of the system in the two different tools, the following metrics have been used: formation error, CPU usage percentage, and the ratio between the real time and the simulation time. The results show the feasibility of using Robot Operating System (ROS) 2 in distributed architectures for multi-agent systems in experiences with real and virtual robots regardless of the number of agents and their nature. However, the two tools under study present different behaviors when the number of virtual agents grows in some of the parameters, and such discrepancies are analyzed.

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.

Positive Emotions, More Than Anxiety or Other Negative Emotions, Predict Willingness to Interact With Robots.

Like early work on human intergroup interaction, previous research on people's willingness to interact with robots has focused mainly on effects of anxiety. However, existing findings suggest that other negative emotions as well as some positive emotions also have effects. This article systematically examines the roles of positive and negative emotions in predicting willingness to interact with robots, using an integrative analysis of data across five studies that use diverse interaction conditions and several types of robots. We hypothesize and find that positive emotions account for more variance than negative emotions. Practically, the findings suggest new strategies for interventions, aimed at increasing positive emotions to increase willingness to engage in intergroup interaction. No existing work has examined whether positive emotions are stronger predictors than negative emotions for willingness for human intergroup interaction, an important topic for future research.

EEG-Controlled Wall-Crawling Cleaning Robot Using SSVEP-Based Brain-Computer Interface.

The assistive, adaptive, and rehabilitative applications of EEG-based robot control and navigation are undergoing a major transformation in dimension as well as scope. Under the background of artificial intelligence, medical and nonmedical robots have rapidly developed and have gradually been applied to enhance the quality of people's lives. We focus on connecting the brain with a mobile home robot by translating brain signals to computer commands to build a brain-computer interface that may offer the promise of greatly enhancing the quality of life of disabled and able-bodied people by considerably improving their autonomy, mobility, and abilities. Several types of robots have been controlled using BCI systems to complete real-time simple and/or complicated tasks with high performances. In this paper, a new EEG-based intelligent teleoperation system was designed for a mobile wall-crawling cleaning robot. This robot uses crawler type instead of the traditional wheel type to be used for window or floor cleaning. For EEG-based system controlling the robot position to climb the wall and complete the tasks of cleaning, we extracted steady state visually evoked potential (SSVEP) from the collected electroencephalography (EEG) signal. The visual stimulation interface in the proposed SSVEP-based BCI was composed of four flicker pieces with different frequencies (e.g., 6 Hz, 7.5 Hz, 8.57 Hz, and 10 Hz). Seven subjects were able to smoothly control the movement directions of the cleaning robot by looking at the corresponding flicker using their brain activity. To solve the multiclass problem, thereby achieving the purpose of cleaning the wall within a short period, the canonical correlation analysis (CCA) classification algorithm had been used. Offline and online experiments were held to analyze/classify EEG signals and use them as real-time commands. The proposed system was efficient in the classification and control phases with an obtained accuracy of 89.92% and had an efficient response speed and timing with a bit rate of 22.23 bits/min. These results suggested that the proposed EEG-based clean robot system is promising for smart home control in terms of completing the tasks of cleaning the walls with efficiency, safety, and robustness.

The multi-variation approach

Abstract This article argues that a multi-variation approach can be a useful supplement to existing ethnographic studies in the field of Human-Robot Interaction (HRI). The multi-variation approach builds on classical ethnographic case studies, where a researcher studies a delimited field in a microstudy of a particular robot, its makers, users, and affected stakeholders. The approach is also inspired by multi-sited studies, where researchers move across fields, adding to the complexity of the ethnographic findings. Whereas both approaches build on analysis of microstudies, the multi-variation approach is further inspired by postphenomenology, where the main aim is to deliberately seek variation – thus again adding to the complexity of the detailed findings. Here, the multivariation approach includes several researchers studying several types of robots across sites. The analytical approach seeks patterns across this complexity – and the claim is that a multi-variation approach has a strength in findings that are systematic and consistent across cases, sites, and variations. The article gives an example of such cross-variation findings in the robot field – namely the tendency for roboticists across cases and robot types to publicly present their robots as more finished and wellfunctioning than they actually are.

Meal Assistance Robot Operated by Detecting Voluntary Closed Eye

The number of people with disabilities is growing in Japan. They are facing many kinds of difficulties in their daily lives. Especially, it is even difficult in having meals for the people with upper limb disabilities. They need system which is able to help them in having meals. There are already several types of robots for meal assist. These are operated with joysticks or touch sensors. However, people with upper limb disabilities can barely operate the robots with full functions. Therefore, a maneuverable meal assistance robot which is easy to operate with an eye-interface is proposed for people with upper limb disabilities. The robot is operated by user’s closed eye. The closed eye is designed to be detected by a web camera connected to control unit based on Raspberry Pi. In addition, the proposed robot with orthogonal structure, that offers simple and stable motions, is able to provide foods to users smoothly. Thus, the system in compact size can complete the food providing effectively.

On the behaviour of low cost laser scanners in HW/SW particle filter SLAM applications

Particle filters (PFs) are computationally intensive sequential Monte Carlo estimation methods with applications in the field of mobile robotics for performing tasks such as tracking, simultaneous localization and mapping (SLAM) and navigation, by dealing with the uncertainties and/or noise generated by the sensors as well as with the intrinsic uncertainties of the environment. However, the application of PFs with an important number of particles has traditionally been difficult to implement in real-time applications due to the huge number of operations they require. This work presents a hardware implementation on FPGA (field programmable gate arrays) of a PF applied to SLAM which aims to accelerate the execution time of the PF algorithm with moderate resource. The presented system is evaluated for different sensors including a low cost Neato XV-11 laser scanner sensor. First the system is validated by post processing data provided by a realistic simulation of a differential robot, equipped with a hacked Neato XV-11 laser scanner, that navigates in the Robot@Factory competition maze. The robot was simulated using SimTwo, which is a realistic simulation software that can support several types of robots. The simulator provides the robot ground truth, odometry and the laser scanner data. Then the proposed solution is further validated on standard laser scanner sensors in complex environments. The results achieved from this study confirmed the possible use of low cost laser scanner for different robotics applications which benefits in several aspects due to its cost and the increased speed provided by the SLAM algorithm running on FPGA.

Learning to Program with Personal Robots

One of the goals of using robots in introductory programming courses is to increase motivation among learners. There have been several types of robots that have been used extensively in the classroom to teach a variety of computer science concepts. A more recently introduced robot designed to teach programming to novice students is the Institute for Personal Robots in Education (IPRE) robot. The author chose to use this robot and study its motivational effects on non-computer science students in a CS0 course. The purpose of this study was to determine whether using the IPRE robots motivates students to learn programming in a CS0 course. After considering various motivational theories and instruments designed to measure motivation, the author used Keller’s Instructional Materials Motivation Survey to measure four components of motivation: attention, relevance, confidence, and satisfaction. Additional items were added to the survey, including a set of open-ended questions. The results of this study indicate that the use of these robots had a positive influence on participants’ attitudes towards learning to program in a CS0 course, but little or no effect on relevance, confidence, or satisfaction. Results also indicate that although gender and students interests may affect individual components of motivation, gender, technical self-perception, and interest in software development have no bearing on the overall motivational levels of students.

Design of a universal robot controller

The paper deals with a general purpose industrial robot controller. Due to the modules of the system is universal. It can be connected to several types of robots, even to CNC, turning-mill or other machines. It was connected to an Adept Scara robot successfully,experimental results will be presented. The basic element of the system is the EMC2 open source robot controller program, which runs in a realtime linux kernel. A PCI card creates the high speed connection between the EMC2 and the machine. DC servo amplifier, digital input and output module, teach pendant, and power electronics designed for the system. The system is RT-middleware (Robotics Technology Middleware)compatible. The RT-middleware is a common robot control platform, which can easily connect different robots to the same network for a common work.

Navegação de robôs utilizando curvas implícitas

Em diversas aplicações robóticas que incluem monitoramento, mapeamento e vigilância, robôs devem seguir caminhos fechados que podem ter formas diversas, determinadas pela aplicação. Neste artigo é proposta uma metodologia para navegação de robôs em tarefas como estas, onde o caminho do robô pode ser definido como a intercessão de cur-vas de nível de determinadas funções. Além do caminho, a lei de controle do robô também é definida por meio de um campo vetorial criado a partir destas funções. A principal contribuição deste artigo é a construção de campos vetoriais em espaços n-dimensionais. Prova-se que um robô holonômico controlado por este campo converge e circula a curva especificada. O artigo mostra ainda que o campo resultante é contínuo e pode ser modificado para manter o módulo da velocidade do robô constante, característica importante para controle de alguns robôs aéreos, como é o caso de aviões não-tripulados. Finalmente, é mostrada uma técnica numérica, baseada na soma ponderada de funções de base radial, para criação das funções que determinam o caminho a ser seguido pelo robô. Simulações realizadas com um robô móvel não-holonômico sujeito a erros de localização ilustram o potencial da técnica para a navegação de diversos tipos de robôs.

Research on Automatic Locomotion Pattern Generation for Modular Robots

Locomotion, one of the most basic robotic functions, has been widely studied for several types of robots. As for self-reconfigurable modular robots, there are two types of locomotion; one type is realized as a series of self-reconfiguration and the other is realized as a whole body motion such as walking and crawling. Even for the latter type of locomotion, designing control method is more difficult than ordinary robots. This is because the module configuration has many degrees of freedom and there are a wide variety of possible configurations. We propose an offline method to generate a locomotion pattern automatically for a modular robot in an arbitrary configuration, which utilizes a neural oscillator as a controller of the joint motor and evolutionary computation method for optimization of the neural oscillator network, which determines the performance of locomotion. We confirm the validity of the method by software simulation and hardware experiments.

Minimum Dynamics Parameters of Robot Models

This article presents a method to determine the minimum set of dynamics parameters of serial link robots. It is based on the use of a new concept ’ τi (i-th joint torque)-identifiable’ to classify the dynamics parameters. The method permits the determination of all the minimum dynamics parameters completely by means of recursive formulations regardless of the values of the geometric parameters of robots. To illustrate the application use of the method, several types of robots are examined.