Alle Publikationen
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2018
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(2018) : A Computational Framework for Integrating Task Planning and Norm Aware Reasoning for Social Robots: 2018 27th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Nanjing, China: IEEE Robotics & Automation Society, S. 282-287
DOI: https://doi.org/10.1109/ROMAN.2018.8525577 Abstract: Autonomous robots are envisioned to increasingly become part of our lives in the house, restaurants, hospitals and offices. Additionally, self-driving cars will be soon appearing in city streets and highways and they will have to interact with cars driven by humans as well as other self-driving cars. In these settings the robots not only need to efficiently perform their tasks but also be able to interact with humans in socially appropriate ways. To accomplish this, robots must be able to reason not only on how to perform their tasks, but also incorporate societal values, social norms and legal rules so they can gain human acceptability and trust. Moreover, interactions with these robots will be long term. Long-term human interaction with robots as well as robot combined reasoning about both tasks and social norms generate multiple modeling and computational challenges. In this paper, we address one of the most important of these challenges, namely what is an appropriate and scalable computational framework that enables simultaneous task and normative reasoning. In particular, we report on our work on a novel computational framework, Modular Normative Markov Decision Processes (MNMDP) that integrates reasoning for domain tasks and normative reasoning for long-term autonomy. The MNMDP framework applies normative reasoning considering only the norms that are activated in appropriate contexts, rather than considering the full set of norms, thus significantly reducing computational complexity. The model modularity is also advantageous for long-term human-robot interaction. We present computational experiments that show significant computational improvements as compared with a base Normative Markov Decision Process (MDP) framework that includes the full set of norms.
Keywords: Angemessen(heit) (von Technik), Autonomous automobiles, autonomous robots, Cognition, Computational complexity, Decision theory, human acceptability, human-robot interaction, ieee xplore, inference mechanisms, knowledge based systems, long-term human interaction, Markov processes, MNMDP framework, Mobile robots, modular normative Markov decision processes, norm aware reasoning, normative Markov decision process framework, Normative reasoning, path planning, Planning, robot combined reasoning, self-driving cars, Social Norms, social robots, societal values, Task Analysis, task planning 2017
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(2017) : Socially-aware navigation planner using models of human-human interaction: 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): Lisbon, Portugal: IEEE Robotics & Automation Society, S. 405-410
DOI: https://doi.org/10.1109/ROMAN.2017.8172334 Abstract: In this paper, we revisit a real-time socially-aware navigation planner which helps a mobile robot to navigate alongside humans in a socially acceptable manner. This navigation planner is a modification of nav core package of Robot Operating System (ROS), based upon earlier work and further modified to use only egocentric sensors. The planner can be utilized to provide safe as well as socially appropriate robot navigation. Primitive features including interpersonal distance between the robot and an interaction partner and features of the environment (such as hallways detected in real-time) are used to reason about the current state of an interaction. Gaussian Mixture Models (GMM) are trained over these features from human-human interaction demonstrations of various interaction scenarios. This model is both used to discriminate different human actions related to their navigation behavior and to help in the trajectory selection process to provide a social-appropriateness score for a potential trajectory. This paper presents an evaluation done in simulation while utilizing data from real human interactions.
Keywords: Angemessen(heit) (von Technik), egocentric sensors, Feature extraction, Gaussian Mixture Models, Gaussian processes, human actions, human interactions, human-human interaction demonstrations, human-robot interaction, Humans, ieee xplore, interaction partner, interaction scenarios, mixture models, mobile robot, Mobile robots, nav core package, Navigation, navigation behavior, path planning, primitive features, Real-time systems, Robot Operating System, Robot sensing systems, service robot, social-appropriateness score, socially acceptable manner, socially appropriate robot navigation, socially-aware navigation planner, Trajectory 2016
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(2016) : Mobile robot navigation for human-robot social interaction: 2016 16th International Conference on Control, Automation and Systems (ICCAS): Gyeongju, Korea: IEEE, S. 1298-1303
DOI: https://doi.org/10.1109/ICCAS.2016.7832481 Abstract: Human social interactions are believed to be described by a mathematical model called the Social Force Model (SFM). A variety of mobile robot research has often used the SFM to generate an appropriate navigation behavior. However, to create a mobile robot that moves around in a human-populated environment in a socially acceptable way, it should be stressed that the social conventions are strictly obeyed. This paper proposes an extended SFM between humans and robots, called the Social Relationship Model (SRM), to enable mobile robots to generate navigation paths in a human-like manner. Simulation results show notable advantages of SRM over the Transition based Rapidly Random Tree (T-RRT) path planning algorithm. The proposed method ensures a socially acceptable robot path, one of the most important issues for human-robot symbiosis.
Keywords: Angemessen(heit) (von Technik), Collision avoidance, Force, human-populated environment, human-robot interaction, human-robot social interaction, Human-Robot Symbiosis, ieee xplore, Mathematical model, mobile robot navigation, Mobile robots, Navigation, path planning, service robot, SFM, social force model, social relationship model, SRM, Symbiosis, transition based rapidly random tree, trees (mathematics), T-RRT path planning algorithm -
(2016) : Incorporating perception uncertainty in human-aware navigation: A comparative study: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN): New York City, USA: IEEE, S. 570-577
DOI: https://doi.org/10.1109/ROMAN.2016.7745175 Abstract: In this work, we present a novel approach to human-aware navigation by probabilistically modelling the uncertainty of perception for a social robotic system and investigating its effect on the overall social navigation performance. The model of the social costmap around a person has been extended to consider this new uncertainty factor, which has been widely neglected despite playing an important role in situations with noisy perception. A social path planner based on the fast marching method has been augmented to account for the uncertainty in the positions of people. The effectiveness of the proposed approach has been tested in extensive experiments carried out with real robots and in simulation. Real experiments have been conducted, given noisy perception, in the presence of single/multiple, static/dynamic humans. Results show how this approach has been able to achieve trajectories that are able to keep a more appropriate social distance to the people, compared to those of the basic navigation approach, and the human-aware navigation approach which relies solely on perfect perception, when the complexity of the environment increases. Accounting for uncertainty of perception is shown to result in smoother trajectories with lower jerk that are more natural from the point of view of humans.
Keywords: Angemessen(heit) (von Technik), Computational modeling, Detectors, dynamic humans, fast marching method, human-aware navigation, human-robot interaction, ieee xplore, Mobile robots, Navigation, noisy perception, path planning, perception uncertainty, Probabilistic logic, probabilistic modelling, Probability, Proposals, Robots, social costmap, social navigation performance, social path planner, social robotic system, static humans, trajectories, trajectory control, uncertain systems, uncertainty, uncertainty factor
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