Zoekresultaten

Junior soccer simulation - providing all primary and secondary students access to educational robotics

The use of robots as educational tools provide a stimulating environment for students. Some robotics competitions focus on primary and secondary school aged children, and serve as a motivation factor for students to get involved in educational robotics activities. But, in most competitions students are required to deal with robot design, construction and programming. Although very appealing, many students cannot participate on robotics competitions because they cannot afford robotics kits and their school do not have the necessary equipment. Because of that, several students have no access to educational robotics, especially on developing countries. To minimize this problem and contribute to education equality, we present a proposal for a new league for the robotics competitions: The Junior Soccer Simulation league (JSS). In such a league, students program virtual robots in a similar way that they would program their real ones. Because there is no hardware involved, costs are very low and participants can concentrate on software development and robot's intelligence improvement. Finally, because soccer is the most popular sport in the world, we believe JSS will be a strong motivator for students to get involved with robotics. In this paper we present the simulator that was developed (ROSOS) and discuss some ideas for the adoption of a Junior Soccer Simulation competition.

Deep Reinforcement Learning Applied to a Robotic Pick-and-Place Application

Industrial robot manipulators are widely used for repetitive applications that require high precision, like pick-and-place. In many cases, the movements of industrial robot manipulators are hard-coded or manually defined, and need to be adjusted if the objects being manipulated change position. To increase flexibility, an industrial robot should be able to adjust its configuration in order to grasp objects in variable/unknown positions. This can be achieved by off-the-shelf vision-based solutions, but most require prior knowledge about each object tobe manipulated. To address this issue, this work presents a ROS-based deep reinforcement learning solution to robotic grasping for a Collaborative Robot (Cobot) using a depth camera. The solution uses deep Q-learning to process the color and depth images and generate a greedy policy used to define the robot action. The Q-values are estimated using Convolutional Neural Network (CNN) based on pre-trained models for feature extraction. Experiments were carried out in a simulated environment to compare the performance of four different pre-trained CNNmodels (RexNext, MobileNet, MNASNet and DenseNet). Results showthat the best performance in our application was reached by MobileNet,with an average of 84 % accuracy after training in simulated environment.

Moving robotics competitions virtual:

For almost 25 years, the goal of the RoboCup has been to build soccer robots capable of winning against the FIFA World Champion of 2050. To foster the participation of the next generation of roboticists, the RoboCupJunior competition takes place in parallel and provides a similar challenge of appropriate difficulty for high school students. RoboCupJunior has three main categories: Soccer, Rescue and OnStage. For the Soccer category, participants need to design, build and program a team of autonomous robots to play soccer against an opponent team of robots. The competition is physical in nature, since it assumes physical robots playing against one another. In 2020 and 2021, the COVID-19 pandemic has made it difficult for a competition of this type to take place, due to obvious restrictions on physical gatherings. To allow for some sort of participation, and inspired by positive experience of the larger RoboCup community, the Organizing Committee of RoboCupJunior Soccer has explored porting a portion of the challenge to a simulated environment. Many of the existing environments, however, are built for higher education/research teams competitions or research, making them complex to deploy and generally unsuitable for high school students. In this paper we present the development of SoccerSim, a simulated environment for RoboCupJunior Soccer, based on the Webots open-source robotics simulator. We also discuss how the participation of students was key for its development and present a summary of the competition rules. We further describe the case study of utilizing SoccerSim first as a testbed for a Demo competition, and later as part of RoboCup Worldwide 2021. The participation of more than 60 teams from over 20 countries suggests that SoccerSim provides an affordable alternative to physical robotics platforms, while being stable enough to support a diverse userbase. The experience of using SoccerSim at RoboCupJunior Worldwide 2021 suggests that a simulated environment significantly lowers the barrier to entry, as evidenced by the participation of many teams that have not participated before. To make it easy for similar competitions to take place in the future, we made the code of SoccerSim available as open-source, as well as the associated tooling required for using it in a tournament.

RoSoS-a free and open-source robot soccer simulator for educational robotics

The use of robots as educational tools provides a stimulating environment for students. Some robotics competitions focus on primary and secondary school aged children, and serve as motivation for students to get involved in educational robotics activities. Although very appealing, many students cannot participate on robotics competitions because they cannot afford robotics kits. Hence, several students have no access to educational robotics, especially on developing countries. To minimize this problem and contribute to education equality, we have created RoSoS Robot Soccer Simulator, in which students program virtual robots in a similar way that they would program their real ones. In this chapter we explain some technical details of RoSoS and discuss the implementation of a new league for the robotics competitions: Junior Soccer Simulation league (JSS). Because soccer is the most popular sport in the world, we believe JSS will be a strong motivator for students to get involved with robotics.

Robotics Simulation Labs

Human-robot co-creativity: a scoping review

This review is the first step in a long-term research project exploring how social robotics and AI-generated content can contribute to the creative experiences of older adults, with a focus on collaborative drawing and painting. We systematically searched and selected literature on human-robot co-creativity, and analyzed articles to identify methods and strategies for researching co-creative robotics. We found that none of the studies involved older adults, which shows the gap in the literature for this often involved participant group in robotics research. The analyzed literature provides valuable insights into the design of human-robot co-creativity and informs a research agenda to further investigate the topic with older adults. We argue that future research should focus on ecological and developmental perspectives on creativity, on how system behavior can be aligned with the values of older adults, and on the system structures that support this best.