World Modeling for Autonomous Systems

Gheta, Ioana; Heizmann, Michael; Belkin, Andrey; Beyerer, Jürgen

doi:10.1007/978-3-642-16111-7_20

Cited by 11 publications

(9 citation statements)

References 28 publications

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“…in [44] authors propose an approach for modeling cooperative intelligent vehicles by means of modeling constructs enabling the specification of uncertainty degrees for attributes of the modeled objects. In [45] authors propose an approach to support world modeling for autonomous systems. The main characteristic of the proposed technique is that "it models uncertainties by probabilities, which are handled by a Bayesian framework including instantiation, deletion and update procedures".…”

Section: Safety Management -World Knowledgementioning

confidence: 99%

Safety for mobile robotic systems: A systematic mapping study from a software engineering perspective

Bozhinoski

Ruscio

Malavolta

et al. 2019

Journal of Systems and Software

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Robotic research is making huge progress. However, existing solutions are facing a number of challenges preventing them from being used in our everyday tasks: (i) robots operate in unknown environments, (ii) robots collaborate with each other and even with humans, and (iii) robots shall never injure people or create damages. Researchers are targeting those challenges from various perspectives, producing a fragmented research landscape. We aim at providing a comprehensive and replicable picture of the state of the art from a software engineering perspective on existing solutions aiming at managing safety for mobile robotic systems. We apply the systematic mapping methodology on an initial set of 1,274 potentially relevant research papers, we selected 58 primary studies and analyzed them according to a systematicallydefined classification framework. This work contributes with (i) a classification framework for methods or techniques for managing safety when dealing with the software of mobile robotic systems (MSRs), (ii) a map of current software methods or techniques for software safety for MRSs, (iii) an elaboration on emerging challenges and implications for future research, and (iv) a replication package for independent replication and verification of this study. Our results confirm that generally existing solutions are not yet ready to be used in everyday life. There is the need of turn-key solutions ready to deal with all the challenges mentioned above.

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Section: Safety Management -World Knowledgementioning

confidence: 99%

Safety for mobile robotic systems: A systematic mapping study from a software engineering perspective

Bozhinoski

Ruscio

Malavolta

et al. 2019

Journal of Systems and Software

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“…In case of failure the symbolic planner is forced to re-plan. Another approach for modeling object data has been proposed by Belkin (2010); Gheta et al (2010). The authors propose a world representation that is fed by an object-oriented prior knowledge base and the robots sensor inputs to represent internal robot states.…”

Section: Related Workmentioning

confidence: 99%

Cognitive Reasoning for Compliant Robot Manipulation

Leidner

2019

Springer Tracts in Advanced Robotics

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The findings were elaborated in cooperation with the Institute for Artificial Intelligence at the University of Bremen. This exceptional alliance between two of the world's leading research facilities on artificial intelligence and robotics enabled me to realize this work. Accordingly, I would first like to express my utmost gratitude to my supervisors Prof. Michael Beetz and Prof. Alin Albu-Schäffer for the opportunity to live out this relationship under their guidance. In addition, I would like to thank Christoph Borst for his trust in my qualities as a robotics researcher that allowed me to work in one of the most inspiring environments. My special thanks go to Florian Schmidt, who introduced me to the world of robotics and continually supported me during my research. Furthermore, I would like to thank Dr. Alexander Dietrich, which whom I collaborated in several publications leading to a better understanding of the interconnections between high-level reasoning and low-level control. Thanks to Georg Bartels, for the interesting and fruitful discussions during our research stays, which resulted in many valuable ideas. Thanks to my former students Peter Birkenkampf and Wissam Bejjani for their support. My deep gratitude goes to the entire support team of Rollin' Justin for the maintenance of the robot, which are

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“…For the situation assessment process, probabilistic methods like hidden Markov models can be used (see Meyer-Delius et al (2009)), but they are strongly dependent on training data. In Gheţa et al (2010), a Bayesian method for the association of observations to objects is presented, and in Glinton et al (2006), Markov random fields are used to model contextual relationships and maximum a posteriori labeling is used to infer intentions of the observed entities. In this section, we will clarify the separation of the real world and the world model represented in the system and introduce the concepts of objects, scenes, relations, and situations, which are necessary for the internal representation of the observed entities in the environment.…”

Section: Domains Of the World Modelingmentioning

confidence: 99%