Robot Competition Research Articles

Prototipe Robot SUMO Otonom dalam Mengenali Object Musuh berbasis Sensor Ultrasonic

The current competition is not only done by humans, but has entered into interference from technology, one of which is robotics technology. One of the competitions is the sumo robot competition, the purpose of making this sumo robot is to be able to move independently or autonomously and be able to detect enemies and push enemies out of the arena, so that the functionalities of the robot are similar to sumo wrestlers and after that can be included in the competition. This sumo robot uses an arduino nano microcontroller as the brain of the robot, five ultrasonic sensors and two proximity sensors, in technical terms the assembly begins with the design, assembly, programming and finally testing. Robot testing is done by testing the characteristics of the movement based on sensor input. The result is the robot will react if there is an object with a radius of 75 cm from the robot and the robot also reacts when the floor surface is light colored.

VR platform enabling crowdsourcing of embodied HRI experiments – case study of online robot competition

The COVID-19 pandemic has made it difficult to conduct research involving human-robot interactions (HRIs). As a result, many robot competitions have been canceled in the past year. To address this problem, we propose a cloud-based VR platform for the crowdsourcing of embodied cognition with multiple human users and a virtual robot. The feasibility of the platform is evaluated from the latency of the interactive events and the motions of avatars, based on the number of users logging in to the VR scene and the distance between the local and server environments. We also discuss the feasibility of our system when dealing with large-scale datasets in embodied HRI experiments.

The MRS UAV System: Pushing the Frontiers of Reproducible Research, Real-world Deployment, and Education with Autonomous Unmanned Aerial Vehicles

We present a multirotor Unmanned Aerial Vehicle control (UAV) and estimation system for supporting replicable research through realistic simulations and real-world experiments. We propose a unique multi-frame localization paradigm for estimating the states of a UAV in various frames of reference using multiple sensors simultaneously. The system enables complex missions in GNSS and GNSS-denied environments, including outdoor-indoor transitions and the execution of redundant estimators for backing up unreliable localization sources. Two feedback control designs are presented: one for precise and aggressive maneuvers, and the other for stable and smooth flight with a noisy state estimate. The proposed control and estimation pipeline are constructed without using the Euler/Tait-Bryan angle representation of orientation in 3D. Instead, we rely on rotation matrices and a novel heading-based convention to represent the one free rotational degree-of-freedom in 3D of a standard multirotor helicopter. We provide an actively maintained and well-documented open-source implementation, including realistic simulation of UAV, sensors, and localization systems. The proposed system is the product of years of applied research on multi-robot systems, aerial swarms, aerial manipulation, motion planning, and remote sensing. All our results have been supported by real-world system deployment that shaped the system into the form presented here. In addition, the system was utilized during the participation of our team from the CTU in Prague in the prestigious MBZIRC 2017 and 2020 robotics competitions, and also in the DARPA SubT challenge. Each time, our team was able to secure top places among the best competitors from all over the world. On each occasion, the challenges has motivated the team to improve the system and to gain a great amount of high-quality experience within tight deadlines.

An autonomous mobile manipulator to build outdoor structures consisting of heterogeneous brick patterns

This paper describes the implementation of an autonomous mobile manipulator to build outdoor structures consisting of heterogeneous brick patterns, finding applications in different industrial automation, manufacturing and civil construction scenarios. This system was developed for the Mohamed Bin Zayed International Robotics Challenge (MBZIRC) 2020, to demonstrate the novel real-world application of constructing structures using teams of robots, showcasing once again the role of major scientific competitions in advancing the state of the art towards exploring solutions to open problems. The paper presents in detail the hardware and software architectures of the developed mobile manipulator, integrating different research results and developments into a functional complex robot system, while proposing methods to detect, approach and manipulate differently sized/colored bricks to build a wall of predefined pattern given to the robot just before the building task starts.Article HighlightsFull system description of an autonomous mobile manipulator for construction tasks tested in a realistic settingAlgorithms for detection, localization, picking and placement of heterogeneous building blocks to form large structuresVersatile service robot capable of smooth adaptation to other functions developed through scientific robot competitions

INVESTIGATING POTENTIALITIES OF FLL (FIRST LEGO LEAGUE) COMPETITION IN SCHOOL LEARNING PROCESS OF BASIC EDUCATION STUDENTS

This work addresses the use of the educational robotics as learning tools. The paper aims to evaluate the possible contributions of the First Lego League (FLL) robotics competition to develop students knowledge and required skills for good professionals. To achieve the research objective, this article presents a study that provides objective data based on the opinions of teachers and students that participated of the FLL. The data analysis strongly indicates that both teachers and students believe in FLL potential to promote school performance and the development of the skills of a good professional.

Do educational robotics competitions impact students’ learning?

The development of robot technology has grown rapidly. Robots have been widely used in various aspects to help human’s interests. In the education sector, robots have also been used as a learning tool to assist in studying fields such as science and technology. Currently, to encourage the development of robots in the education sector, robot competitions are held with various kinds of events. The types of robots developed to participate in robot competitions are also varied, such as mobile robot contest, modular robot contest, humanoid robot contest, flying robot contest, underwater robot contest, innovation robot contest, brick robot contest, and VR robot contest. The robot competition events are held nationally and internationally. The purposes of this study were to identify what kind of skills obtained by students after following the learning process using educational robotics competitions and to determine the appropriate learning model for the use of educational robotics competitions in studying the field of science and technology. This research was a literature review research. The research method was the Comprehensive Literature Review (CLR). This method has three phases such as 1) exploring phase, 2) interpretation phase, and 3) communication phase. The results showed that the learning model that was widely used in educational robotics competitions was project-based learning and was followed by problem-based learning. The skills obtained were to assist understanding science and technology, to develop computer programming skills, to sharpen problem-solving capability, to foster creativity and innovation, to bridge the gap between theory and practice, and to practice teamwork and social skills.

Autonomous planning based on spatial concepts to tidy up home environments with service robots

ABSTRACT Tidy-up tasks by service robots in home environments are challenging in robotics applications because they involve various interactions with the environment. In particular, robots are required not only to grasp, move, and release various home objects but also to plan the order and positions for placing the objects. In this paper, we propose a novel planning method that can efficiently estimate the order and positions of the objects to be tidied up by learning the parameters of a probabilistic generative model. The model allows a robot to learn the distributions of the co-occurrence probability of the objects and places to tidy up using the multimodal sensor information collected in a tidied environment. Additionally, we develop an autonomous robotic system to perform the tidy-up operation. We evaluate the effectiveness of the proposed method by an experimental simulation that reproduces the conditions of the Tidy Up Here task of the World Robot Summit 2018 international robotics competition. The simulation results show that the proposed method enables the robot to successively tidy up several objects and achieves the best task score among the considered baseline tidy-up methods.

Estimating robot strengths with application to selection of alliance members in FIRST robotics competitions

Since the inception of the FIRST Robotics Competition (FRC) and its special playoff system, robotics teams have longed to appropriately quantify the strengths of their designed robots. The FRC includes a playground draft-like phase (alliance selection), arguably the most game-changing part of the competition, in which the top-8 robotics teams in a tournament based on the FRC’s ranking system assess potential alliance members for the opportunity of partnering in a playoff stage. In such a three-versus-three competition, several measures and models have been used to characterize actual or relative robot strengths. However, existing models are found to have poor predictive performance due to their imprecise estimates of robot strengths caused by a small ratio of the number of observations to the number of robots. A more general regression model with latent clusters of robot strengths is, thus, proposed to enhance their predictive capacities. Two effective estimation procedures are further developed to simultaneously estimate the number of clusters, clusters of robots, and robot strengths. Meanwhile, some measures are used to assess the predictive ability of competing models, the agreement between published FRC measures of strength and model-based robot strengths of all, playoff, and FRC top-8 robots, and the agreement between FRC top-8 robots and model-based top robots. Moreover, the stability of estimated robot strengths and accuracies is investigated to determine whether the scheduled matches are excessive or insufficient. In the analysis of qualification data from the 2018 FRC Houston and Detroit championships, the predictive ability of our model is also shown to be significantly better than those of existing models. Teams who adopt the new model can now appropriately rank their preferences for playoff alliance partners with greater predictive capability than before.

Tomato-Harvesting Robot Competition: Aims and Developed Robot of 6th Competitions

Tomato-Harvesting Robot Competition: Aims and Developed Robot of 6th Competitions

Team Activity of Robot Competition of Simulated Robot in World Robot Summit 2020

World Robot Summit (WRS) has several robot competitions, and we will participate it in the infrastructure and disaster response category. Participating teams develop their robot system by teleoperation and/or autonomous operation and run it in a set of courses modelling and simplifying disaster responding situations. The authors will attend the challenge of the tunnel disaster response and recovery, in which we are requested to achieve an investigation and rescue scenario of a tunnel fire with simulated robots. As preparation, we develop simulated robot models and corresponding software as a team. In this article, we report out activity to the robot competition and student’s project-based learning by joining it.

Space Mining Robot Prototype for NASA Robotic Mining Competition Utilizing Systems Engineering Principles

The 2017 National Aeronautics and Space Ad-ministration (NASA) Robotic Mining Competition (RMC) is an outstanding opportunity for engineering students to imple-ment all the knowledge and experience that they gained in the undergraduate years, in building a robot that will provide an intellectual insight to NASA, to develop innovative robotic excavation concepts. For this competition, multiple universities from all over the U.S. will create teams of students and faculty member to design and build a mining robot that can traverse, mine, excavate at least 10 kg of regolith, then deposit it in a bin in the challenging simulated Martian terrain. Our team’s goal is to improve on our current design, and overcome DustyTRON 2.0’s limitations by analyzing them and implementing new engineering solutions. The process to improve this system will enable our team members to learn mechanical, electrical, and software engineering. DustyTRON 3.0 is divided into three sub-teams, namely, Mechanical, Circuitry, Software sub-teams. Mechanical team focused on solving the mechanical structure, robot mobility, stability and weight distribution. Circuitry team focused on the electrical components such as batteries, wiring, and motors. The Software team focused on programming the NVidia TK1, Arduino controller, and cameras integration. This paper will outline the detailed work following systems engineering principles to complete this project, from research, to design process and robot building compete at the Kennedy Space Center. Only 54 teams were invited to participate from allover the US and DustyTRON team represented the state of Texas and placed the 29th and awarded the “Innovative Design” award.

Case Study of AI Education at an Underwater Robot Competition

Case Study of AI Education at an Underwater Robot Competition

Yusuf Azeem Is Not a Hero by Saadia Faruqi

Reviewed by: Yusuf Azeem Is Not a Hero by Saadia Faruqi Elizabeth Bush Faruqi, Saadia Yusuf Azeem Is Not a Hero. Quill Tree/HarperCollins, 2021 [368p] Trade ed. ISBN 9780062943255 $16.99 E-book ed. ISBN 9780062943248 $8.99 Reviewed from digital galleys R Gr. 4-7 Over the two decades since the September 11th attacks, the Muslim and non-Muslim residents of the small town of Frey, Texas have coexisted in apparent cordiality. On this twentieth anniversary of the tragedy, though, rabid bigot Trevor Grant is organizing a group of Patriot Sons to use the town’s “Never Forget” commemoration theme to kindle enough hatred to run the Muslim population out of town. It’s a lot for middle-schooler Yusuf Azeem to process; all he wants is to lay low when parents enlist their kids to help with construction of their new mosque, to avoid being bullied at school by Grant’s son, and to organize a team that will win an award at the Texas Robotics Competition. As the Frey atmosphere grows steadily more toxic, though, it’s clear that an event that merely registers as ancient history to Yusuf is very much a raw wound for adults. His uncle helps him understand what his family and Muslim neighbors endured in 2001, why they are now divided on how to handle a resurgence of bigotry, and why he may actually need to stand up alongside fellow Muslims and their community allies to neutralize the Patriot Sons’ vitriol. Although conversations are sometimes stilted, Faruqi effectively probes complexities of radical activism vs. peaceful accommodation as Muslim response to prejudice, as well as the non-Muslim community’s deep discomfort in stepping beyond a bystander role in defense of their neighbors. An author note discusses a 2015 incident that served as inspiration for Yusuf’s story. Copyright © 2021 The Board of Trustees of the University of Illinois

Tomato-Harvesting Robot Competition

Tomato-Harvesting Robot Competition

Simulators in Educational Robotics: A Review

Educational robotics (ER) seems to have a positive effect on students and, in many cases, might help them to successfully assimilate knowledge and skills. Thus, this paper focuses on ER and carries out a literature review on educational robotics simulators with Graphical User Interfaces (GUIs). The review searches for relevant papers which were published in the period 2013–2020 and extracted the characteristics of the simulators used. The simulators that we describe in this article cover various robotic technologies, offering students an easy way to engage with virtual robots and robotics mechanisms, such as wheeled robots or drones. Using these simulators, students might cover their educational needs or prepare themselves for educational robotic competitions by working in as realistic as possible conditions without hardware restrictions. In many cases, simulators might reduce the required cost to obtain a robotic system and increase availability. Focusing on educational robotics simulators, this paper presents seventeen simulators emphasizing key features such as: user’s age, robot’s type and programming language, development platform, capabilities, and scope of the simulator.

Spoken dialogue system development at the dialogue robot competition

Spoken dialogue system development at the dialogue robot competition

A Small Simulated Logistics Transfer Robot Car Structure Design

As a new product of the development of modern science and technology, the research and development of logistics robot has become the focus of social attention. Robot sorting and handling is the designated project of Jiangsu University Robot Competition. According to the requirements of the competition, this paper designs a kind of logistics robot trolley which can identify and grab materials according to a given path and transport them to a predetermined location. The mechanical structure design, driving motor selection and mechanical checking calculation of the car are mainly completed. According to the later experiments, the results show that the desired results can be achieved.

Proposal of Robot Software Platform with High Sustainability

At present, various robotics competitions are being held, including the Tsukuba Challenge. The purpose of participating in a robotics competition is to confirm what can be done with the current technology and to demonstrate new research results. Participating teams often use open source software (OSS) for path planning and autonomous navigation. OSS is advantageous in facilitating participation in robotics competitions. However, applying it to a new robot is difficult when a new research does not involve OSS. In addition, robot systems do not consist only of OSS, and the burden of developing and maintaining other systems is significant. To solve the above problems, a software platform that allows for the addition of research achievements of individual robots is desired. With such a platform, research elements that have already been developed can be shared without the need to develop a new system. This makes it easier to maintain and manage the system and increase its sustainability.

Garbage Detection Using YOLOv3 in Nakanoshima Challenge

Object detectors using deep learning are currently used in various situations, including robot demonstration experiments, owing to their high accuracy. However, there are some problems in the creation of training data, such as the fact that a lot of labor is required for human annotations, and the method of providing training data needs to be carefully considered because the recognition accuracy decreases due to environmental changes such as lighting. In the Nakanoshima Challenge, an autonomous mobile robot competition, it is challenging to detect three types of garbage with red labels. In this study, we developed a garbage detector by semi-automating the annotation process through detection of labels using colors and by preparing training data by changing the lighting conditions in three ways depending on the brightness. We evaluated the recognition accuracy on the university campus and addressed the challenge of using the discriminator in the competition. In this paper, we report these results.

Open-Source Drone Programming Course for Distance Engineering Education

This article presents a full course for autonomous aerial robotics inside the RoboticsAcademy framework. This “drone programming” course is open-access and ready-to-use for any teacher/student to teach/learn drone programming with it for free. The students may program diverse drones on their computers without a physical presence in this course. Unmanned aerial vehicles (UAV) applications are essentially practical, as their intelligence resides in the software part. Therefore, the proposed course emphasizes drone programming through practical learning. It comprises a collection of exercises resembling drone applications in real life, such as following a road, visual landing, and people search and rescue, including their corresponding background theory. The course has been successfully taught for five years to students from several university engineering degrees. Some exercises from the course have also been validated in three aerial robotics competitions, including an international one. RoboticsAcademy is also briefly presented in the paper. It is an open framework for distance robotics learning in engineering degrees. It has been designed as a practical complement to the typical online videos of massive open online courses (MOOCs). Its educational contents are built upon robot operating system (ROS) middleware (de facto standard in robot programming), the powerful 3D Gazebo simulator, and the widely used Python programming language. Additionally, RoboticsAcademy is a suitable tool for gamified learning and online robotics competitions, as it includes several competitive exercises and automatic assessment tools.