Sebastian Rockel

Bio: Sebastian Rockel is an academic researcher from University of Hamburg. The author has contributed to research in topics: Robot & Mobile robot. The author has an hindex of 7, co-authored 10 publications receiving 136 citations.

An Ontology-based Multi-level Robot Architecture for Learning from Experiences

Abstract: One way to improve the robustness and flexibility of robot performance is to let the robot learn from its ex- periences. In this paper, we describe the architecture and knowledge-representation framework for a service robot being developed in the EU project RACE, and present examples illustrating how learning from experi- ences will be achieved. As a unique innovative feature, the framework combines memory records of low-level robot activities with ontology-based high-level seman- tic descriptions.

The RACE Project : Robustness by Autonomous Competence Enhancement

Abstract: This paper reports on the aims, the approach, and the results of the European project RACE. The project aim was to enhance the behavior of an autonomous robot by having the robot learn from conceptualized experiences of previous performance, based on initial models of the domain and its own actions in it. This paper introduces the general system architecture; it then sketches some results in detail regarding hybrid reasoning and planning used in RACE, and instances of learning from the experiences of real robot task execution. Enhancement of robot competence is operationalized in terms of performance quality and description length of the robot instructions, and such enhancement is shown to result from the RACE system.

A multi-robot platform for mobile robots — A novel evaluation and development approach with multi-agent technology

Abstract: In the field of robotics, typical, single-robot systems encounter limits when executing complex tasks. Todays systems often lack flexibility and inter-operability, especially when interaction between participants is necessary. Nevertheless, well developed systems for robotics and for the cognitive and distributive domain are available. What is missing is the common link between these two domains. This work deals with the foundations and methods of a middle layer that joins a multi-agent system with a multi-robot system in a generic way. A prototype system consisting of a multiagent system, a multi-robot system and a middle layer will be presented and evaluated. Its purpose is to combine highlevel cognitive models and information distribution with robot-focused abilities, such as navigation and reactive behavior based artificial intelligence. This enables the assignment of various scenarios to a team of mobile robots.

A novel optical tracking based tele-control system for tabletop object manipulation tasks

Abstract: For a robot serving in a complex environment such as in a restaurant, it is difficult to perform a task like tabletop object manipulation completely by itself, in that some information may be missing. An approach to deal with this is to use a tele-control system and method to control the robot or demonstrate. In this paper, a LeapMotion sensor based non-contact tele-control method is developed for a robot to perform tabletop object manipulation tasks. A coordinate system for mapping from the operation space of the LeapMotion sensor to the workspace of the robot is established. A gesture recognition and action generating algorithm is proposed for control or to demonstrate the motion to the robot. To evaluate the performance of the LeapMotion sensor and proposed method for tele-control of a robot, a comprehensive assessment index based on entropy weighting is proposed. Three common tele-control modes, including demonstration mode, teleoperation mode and semi-teleoperation mode, are developed on a PR2 robot. The experimental results show that the proposed tele-control system is more appropriate for use in task demonstration.

Integrating physics-based prediction with Semantic plan Execution Monitoring

Abstract: Real-world robotic systems have to perform reliably in uncertain and dynamic environments. State-of-the-art cognitive robotic systems use an abstract symbolic representation of the real world for high-level reasoning. Some aspects of the world, such as object dynamics, are inherently difficult to capture in an abstract symbolic form, yet they influence whether the executed action will succeed or fail. This paper presents an integrated system that uses a physics-based simulation to predict robot action results and durations, combined with a Hierarchical Task Network (HTN) planner and semantic execution monitoring. We describe a fully integrated system in which a Semantic Execution Monitor (SEM) uses information from the planning domain to perform functional imagination. Based on information obtained from functional imagination, the robot control system decides whether it is necessary to adapt the plan currently being executed. As a proof of concept, we demonstrate a PR2 able to carry tall objects on a tray without the objects toppling. Our approach achieves this by simulating robot and object dynamics. A validation shows that robot action results in simulation can be transferred to the real world. The system improves on state-of-the-art AI plan-based systems by feeding simulated prediction results back into the execution system.

Automated Planning: Theory and Practice.

Abstract: A translation apparatus is provided which comprises: an inputting section for inputting a source document in a natural language; a layout analyzing section for analyzing layout information including cascade information, itemization information, numbered itemization information, labeled itemization information and separator line information in the source document inputted by the inputting section and specifying a translation range on the basis of the layout information; a translation processing section for translating a source document text in the specified translation range into a second language; and an outputting section for outputting a translated text provided by the translation processing section.

Philosophical Applications of Cognitive Science.Moral Imagination: Implications of Cognitive Science for Ethics

Abstract: Preface Acknowledgments Introduction: How Cognitive Science Changes Ethics 1: Reason as Force: The Moral Law Folk Theory 2: Metaphoric Morality 3: The Metaphoric Basis of Moral Theory 4: Beyond Rules 5: The Impoverishment of Reason: Our Enlightenment Legacy 6: What's Wrong with the Objectivist Self 7: The Narrative Context of Self and Action 8: Moral Imagination 9: Living without Absolutes: Objectivity and the Conditions for Criticism 10: Preserving Our Best Enlightenment Moral Ideals Notes Index

Ego-centered networks and the ripple effect

Abstract: Recent work has demonstrated that many social networks, and indeed many networks of other types also, have broad distributions of vertex degree. Here we show that this has a substantial impact on the shape of ego-centered networks, i.e., sets of network vertices that are within a given distance of a specified central vertex, the ego. This in turn affects concepts and methods based on ego-centered networks, such as snowball sampling and the "ripple effect". In particular, we argue that one's acquaintances, one's immediate neighbors in the acquaintance network, are far from being a random sample of the population, and that this biases the numbers of neighbors two and more steps away. We demonstrate this concept using data drawn from academic collaboration networks, for which, as we show, current simple theories for the typical size of ego-centered networks give numbers that differ greatly from those measured in reality. We present an improved theoretical model which gives significantly better results.

Deliberation for autonomous robots: A survey

Abstract: Autonomous robots facing a diversity of open environments and performing a variety of tasks and interactions need explicit deliberation in order to fulfill their missions. Deliberation is meant to endow a robotic system with extended, more adaptable and robust functionalities, as well as reduce its deployment cost. The ambition of this survey is to present a global overview of deliberation functions in robotics and to discuss the state of the art in this area. The following five deliberation functions are identified and analyzed: planning, acting, monitoring, observing, and learning. The paper introduces a global perspective on these deliberation functions and discusses their main characteristics, design choices and constraints. The reviewed contributions are discussed with respect to this perspective. The survey focuses as much as possible on papers with a clear robotics content and with a concern on integrating several deliberation functions.

Multi-LeapMotion sensor based demonstration for robotic refine tabletop object manipulation task

Abstract: In some complicated tabletop object manipulation task for robotic system, demonstration based control is an efficient way to enhance the stability of execution. In this paper, we use a new optical hand tracking sensor, LeapMotion, to perform a non-contact demonstration for robotic systems. A Multi-LeapMotion hand tracking system is developed. The setup of the two sensors is analyzed to gain a optimal way for efficiently use the informations from the two sensors. Meanwhile, the coordinate systems of the Mult-LeapMotion hand tracking device and the robotic demonstration system are developed. With the recognition to the element actions and the delay calibration, the fusion principles are developed to get the improved and corrected gesture recognition. The gesture recognition and scenario experiments are carried out, and indicate the improvement of the proposed Multi-LeapMotion hand tracking system in tabletop object manipulation task for robotic demonstration.