Auflistung nach Schlagwort "robotics"
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- ZeitschriftenartikelDecentralized decision making in adaptive multi-robot teams(it - Information Technology: Vol. 60, No. 4, 2018) Geihs, Kurt; Witsch, AndreasWe present our decision support middleware PROViDE that facilitates decentralized decision making in multi-robot teams operating in highly dynamic environments with potentially unreliable communication channels and noisy sensors. Achieving an adaptive team behavior in such an environment is a challenge because the specific conditions require a fully decentralized decision process. The design of PROViDE borrows inspiration from human decision making processes. PROViDE supports replication of proposals, conflict resolution, and final team-decision making. For each of these steps a choice of methods is offered to the developer to provide flexibility for different application requirements and characteristics of execution environments. PROViDE is integrated into a comprehensive modeling framework for multi-robot systems. The main contributions of this paper are twofold: For the development of adaptive multi-robot teams we discuss requirements for a middleware that supports decentralized decision making in dynamic and adverse environments, and we demonstrate the effective and coherent integration of a set of domain-dependent decision support protocols into a middleware framework.
- Konferenzbeitragev3dev-prolog – Prolog API for LEGO EV3(INFORMATIK 2019: 50 Jahre Gesellschaft für Informatik – Informatik für Gesellschaft (Workshop-Beiträge), 2019) Schwarz, Sibylle; Wenzel, MarioWe present ev3dev-prolog – an extendable Prolog API to control LEGO EV3 robots – and demonstrate our approach by several examples from introductory robotics courses like obstacle avoidance and Braitenberg vehicles as well as a more complex example. We show how to interleave our API with planning and replanning in Prolog to move a robot through an unknown environment. The presented API is divided into two abstraction layers. Low level predicates control individual sensors and actors, higher level predicates control user-defined robots consisting of several sensors and actors. The connection between the parts of the robot and an SWI-Prolog interpreter running on the robot is established via ev3dev.
- ZeitschriftenartikelFiction meets fact: exploring human-machine convergence in today’s cinematographic culture(i-com: Vol. 23, No. 2, 2024) Endres, Christoph; Frieß, Frederic; Hermann, IsabellaThis article explores the theme of human-machine convergence as portrayed in modern science fiction movies and TV/streaming series and compares them to real-world advancements in robotics, artificial intelligence (AI), and virtual reality (VR). It examines how science fiction often depicts humanoid robots and AI with human-like emotions and intentions, contrasting with the actual technological challenges and ethical considerations in developing intelligent machines. The text discusses the evolution of humanoid robots from fictional portrayals to real-life examples like Boston Dynamics’ Atlas and Tesla’s Optimus. The paper also explores the reverse interaction, where humans become avatars in virtual worlds, and briefly discusses the ethical implications of simulating deceased individuals in digital form. Through this examination, the paper emphasizes the complexity of human-machine convergence and the importance of considering social, ethical, and emotional aspects in technological progress. It concludes by suggesting that while science fiction provides insights into societal fears and hopes regarding technology and thus into ethical and regulative necessities, the real trajectory of human-machine convergence cannot be predicted through film but will be determined by ongoing and after all incidental developments in the real world.
- WorkshopbeitragParameterized Facial Animation for Socially Interactive Robots(Mensch und Computer 2015 – Proceedings, 2015) Wittig, Steffen; Rätsch, Matthias; Kloos, UweSocially interactive robots with human-like speech synthesis and recognition, coupled with humanoid appearance, are an important subject of robotics and artificial intelligence research. Modern solutions have matured enough to provide simple services to human users. To make the interaction with them as fast and intuitive as possible, researchers strive to create transparent interfaces close to human-human interaction. Because facial expressions play a central role in human-human communication, robot faces were implemented with varying degrees of human-likeness and expressiveness. We propose a way to implement a program that believably animates changing facial expressions and allows to influence them via inter-process communication based on an emotion model. This will can be used to create a screen based virtual face for a robotic system with an inviting appearance to stimulate users to seek interaction with the robot.
- ConferencePaperRobotics Software Engineering: A Perspective from the Service Robotics Domain (Summary)(Software Engineering 2021, 2021) García, Sergio; Strüber, Daniel; Brugali, Davide; Berger, Thorsten; Pelliccione, PatrizioWe present our paper published in the proceedings of the ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering 2020. Robots that support humans by performing useful tasks (a.k.a., service robots) are booming worldwide. In contrast to industrial robots, the development of service robots comes with severe software engineering challenges, since they require high levels of robustness and autonomy to operate in highly heterogeneous environments. As a domain with critical safety implications, service robotics faces a need for sound software development practices. In this paper, we present the first large-scale empirical study to assess the state of the art and practice of robotics software engineering. We conducted 18 semi-structured interviews with industrial practitioners working in 15 companies from 9 different countries and a survey with 156 respondents (from 26 countries) from the robotics domain. Our results provide a comprehensive picture of (i) the practices applied by robotics industrial and academic practitioners, including processes, paradigms, languages, tools, frameworks, and reuse practices, (ii) the distinguishing characteristics of robotics software engineering, and (iii) recurrent challenges usually faced, together with adopted solutions. The paper concludes by discussing observations, derived hypotheses, and proposed actions for researchers and practitioners.
- KonferenzbeitragTalk to your Cobot: faster and more efficient error-handling in a robotic system with a multi-modal Conversational Agent(Proceedings of Mensch und Computer 2024, 2024) Schwarz, David; Zarcone, Alessandra; Laquai, FlorianCollaborative robot (cobot) systems are expected to be easy to operate. However, reacting to an error message may not be as intuitive as operating the cobot. This paper explores the integration of a multi-modal conversational agent (text, touch and voice) into a robotic system to improve the robot-user interaction during error handling. The conversational agent enables text- and voice-based interactions to improve user experience and efficiency. We evaluate a prototype in a user test with experts and novices in order to assess its effectiveness, usability, and impact on user-robot interaction and show that conversational agents can enhance collaboration between robots and users, particularly benefiting novices.
- TextdokumentTraining a deep policy gradient-based neural network with asynchronous learners on a simulated robotic problem(INFORMATIK 2017, 2017) Lötzsch, Winfried; Vitay, Julien; Hamker, FredRecent advances in deep reinforcement learning methods have attracted a lot of attention, because of their ability to use raw signals such as video streams as inputs, instead of pre-processed state variables. However, the most popular methods (value-based methods, e.g. deep Q-networks) focus on discrete action spaces (e.g. the left/right buttons), while realistic robotic applications usually require a continuous action space (for example the joint space). Policy gradient methods, such as stochastic policy gradient or deep deterministic policy gradient, propose to overcome this problem by allowing continuous action spaces. Despite their promises, they suffer from long training times as they need huge numbers of interactions to converge. In this paper, we investigate in how far a recent asynchronously parallel actor-critic approach, initially proposed to speed up discrete RL algorithms, could be used for the continuous control of robotic arms. We demonstrate the capabilities of this end-to-end learning algorithm on a simulated 2 degrees-of-freedom robotic arm and discuss its applications to more realistic scenarios.