iDriver - Human Machine Interface for Autonomous Cars

Modern cars are equipped with a variety of sensors, advanced driver assistance systems and user interfaces nowadays. To benefit from these systems and to optimally support the driver in his monitoring and decision making process, efficient human-machine interfaces play an important part. This paper describes the second release of iDriver, an iPad software solution which was developed to navigate and remote control autonomous cars, to give access to live sensor data and useful data about the car state, as there are, e.g., current speed, engine and gear state. The software was used and evaluated in our two fully autonomous research cars “Spirit of Berlin” and “Made in Germany”

Remote controlling an autonomous car with an iPhone

This paper describes iDriver, an iPhone software to remote control “Spirit of Berlin”. “Spirit of Berlin” is a completely autonomous car developed by the Free University of Berlin which is capable of unmanned driving in urban areas. iDriver is an iPhone application sending control packets to the car in order to remote control its steering wheel, gas and brake pedal, gear shift and turn signals. Additionally, a video stream from two top-mounted cameras is broadcasted back to the iPhone

Driving an autonomous car with eye tracking

This paper describes eyeDriver, a hardware and software setup to drive an autonomous car with eye movement. The movement of the operator’s iris is tracked with an infrared sensitive camera built onto a HED4 interface by SMI. The position of the iris is then propagated by eyeDriver to control the steering wheel of “Spirit of Berlin”, a completely autonomous car developed by the Free University of Berlin which is capable of unmanned driving in urban areas

Adaptive Perception, State Estimation, and Navigation Methods for Mobile Robots

In this cumulative habilitation, publications with focus on robotic perception, self-localization, tracking, navigation, and human-machine interfaces have been selected. While some of the publications present research on a PR2 household robot in the Robotics Learning Lab of the University of California Berkeley on vision and machine learning tasks, most of the publications present research results while working at the AutoNOMOS-Labs at Freie Universität Berlin, with focus on control, planning and object tracking for the autonomous vehicles "MadeInGermany" and "e-Instein"

Keeping Autonomous Driving Alive: An Ethnography of Visions, Masculinity and Fragility

In 'Keeping autonomous driving alive', the author studies the relationships between researchers and artefacts held together by contested visions. Drawing on ethnographic fieldwork in a pioneering research project in Germany, he argues we can make sense of technological visions only if we simultaneously grasp the role of care, gender, and narrative in sustaining technological research. Instead of focusing on the genesis and expansion of sociotechnical assemblages, the book offers a radically new alternative to the study of visions. Building on literature from Science & Technology Studies, Science Communication, and Gender Studies, Göde Both investigates the ambivalence and fragility of technological visions, video demonstrations, and street trials in the hands of researchers invested in self-driving cars. Keeping autonomous driving alive will be of interest to sociologists and anthropologists of technology, gender, and mobility. It is essential reading for those concerned with uncertainty in technological research and with conflicting demands in communicating science. The book provides scholars within the fields of robotics, artificial intelligence, and automotive engineering a means of reflecting on their involvement in self-driving cars. Keeping autonomous driving alive offers science, technology, mobility, and automotive journalists a unique perspective on the present realities of a futuristic technology

Keeping Autonomous Driving Alive

InKeeping autonomous driving alive, Göde Both studies the relationships between researchers and artefacts held together by contested visions. Drawing on ethnographic fieldwork in a pioneering research project in Germany, he argues we can make sense of technological visions only if we simultaneously grasp the role of care, gender, and narrative in sustaining technological research.; Eine radikal neue Alternative zum Studium von Visionen: Aufbauend auf Literatur aus den Bereichen Science & Technology Studies, Wissenschaftskommunikation und Gender Studies untersucht der Autor die Ambivalenz und Fragilität von technologischen Visionen, Videodemonstrationen und Straßenversuchen in den Händen von Forschenden, die sich mit selbstfahrenden Autos beschäftigen. Das Buch ist für Soziolog*innen und Anthropolog*innen mit Fokus auf Technik, Geschlecht und Mobilität von interessant, die sich mit der Unsicherheit in der technologischen Forschung und mit den widersprüchlichen Anforderungen bei der Vermittlung von Wissenschaft beschäftigen. Gleichzeitig bietet die Studie Wissenschaftler*innen in den Bereichen Robotik, künstliche Intelligenz und Automobiltechnik eine Möglichkeit, über ihre Beteiligung am selbstfahrenden Auto nachzudenken

Keeping Autonomous Driving Alive

InKeeping autonomous driving alive, Göde Both studies the relationships between researchers and artefacts held together by contested visions. Drawing on ethnographic fieldwork in a pioneering research project in Germany, he argues we can make sense of technological visions only if we simultaneously grasp the role of care, gender, and narrative in sustaining technological research.; Eine radikal neue Alternative zum Studium von Visionen: Aufbauend auf Literatur aus den Bereichen Science & Technology Studies, Wissenschaftskommunikation und Gender Studies untersucht der Autor die Ambivalenz und Fragilität von technologischen Visionen, Videodemonstrationen und Straßenversuchen in den Händen von Forschenden, die sich mit selbstfahrenden Autos beschäftigen. Das Buch ist für Soziolog*innen und Anthropolog*innen mit Fokus auf Technik, Geschlecht und Mobilität von interessant, die sich mit der Unsicherheit in der technologischen Forschung und mit den widersprüchlichen Anforderungen bei der Vermittlung von Wissenschaft beschäftigen. Gleichzeitig bietet die Studie Wissenschaftler*innen in den Bereichen Robotik, künstliche Intelligenz und Automobiltechnik eine Möglichkeit, über ihre Beteiligung am selbstfahrenden Auto nachzudenken

Traffic cones detection for autonomous ground vehicle

Jelajah V-18 is an autonomous vehicle prototype where can navigate autonomously using Global Positioning System (GPS) for long-distance navigation and can find out the surrounding conditions to navigate short distances using cameras and proximity sensors. The vehicle also has a system that can search and recognize a static object using an image processing system. This research focuses on the detection of an objects in the form of traffic cones using the (Hue, Saturation, Value) HSV method to recognize objects by the color, then with the binary method the image of the object will be converted back to get the edges of the object shape and contour where the system can recognize the shape of the object. Based on the implementation and experiments conducted, the robot can detect traffic cone objects with a success rate of 100 percent at a distance of 1-6 meters and 35.67 percent at a distance of 7 meters

Dashboard interativa do estado global do ATLASCAR2

The transportation industry has deployed new efforts to make our driving experience safer and more comfortable. Nowadays, one developed solution points to dashboards. These devices are an Advanced Driver-Assistance System that allows the users to check information regarding the vehicle that transports them through a dynamic display. Within the ATLAS project, the present dissertation aims to create a dashboard for the ATLASCAR2. Given this need, a new power solution for the central process unit responsible for booting all external installed equipment was installed first. The electric board already in place presented some limitations. Therefore, a new one was installed and placed on the vehicle’s trunk. Next, the car was equipped with an inverter that withdraws energy from the vehicle’s lead battery to feed the computer. Then, an information network built upon a ROS architecture had to be created to feed information from the car’s in-built systems to the dashboard display. The Controller Area Network bus of the vehicle was used for this purpose. This work presents the developed solution and all features embedded in it. In addition, a field test was performed, which helped to evaluate the new solution’s functionality.A indústria automóvel tem desenvolvido inúmeros esforços para tentar tornar a nossa experiência de condução mais segura e confortável. Atualmente, uma das soluções desenvolvidas são ”dashboards”. Estes dispositivos são Sistemas Avançados de Assistência ao Condutor que permitem aos utilizadores obterem todas as informações relativas ao estado do veículo que os transporta através de um ”display” dinâmico. No âmbito do projeto ATLAS, esta dissertação tem como objetivo criar uma dashboard para o ATLASCAR2. Tendo em vista este projeto, primeiro foi instalada uma nova solução de energia para a unidade central de processamento do veículo, responsável pelo funcionamento dos equipamentos instalados. O antigo quadro elétrico do carro apresentava algumas limitações. Por essa razão, foi instalado um novo quadro e colocado no porta-malas do veículo. Em seguida, o ATLASCAR2 foi equipado com um inversor que retira energia da bateria de chumbo do veículo para alimentar o computador. Numa segunda fase, foi criada uma nova rede de informação baseada numa arquitetura ROS que fornece o estado dos sistemas integrados no carro ao display da dashboard. O barramento Controller Area Network do veículo foi utilizado para este fim. Este trabalho apresenta a solução desenvolvida e todas as funcionalidades nela incorporada. Por fim. foi realizado um teste que auxiliou na avaliação da usabilidade da nova solução.Mestrado em Engenharia Mecânic