Lothar Hotz

Bio: Lothar Hotz is an academic researcher from Hitec. The author has contributed to research in topics: Ontology (information science) & Specialization (logic). The author has an hindex of 2, co-authored 6 publications receiving 69 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.

Adaptive Autonomous Machines - Requirements and Challenges.

Abstract: In mechanical and plant engineering, the general challenge is to achieve flexibility in order to process changes in the requirements or operating conditions of a machine on the site of the plant operator. Changes to the machine and its configuration require the operator to work together with the machine builder (or plant constructor for several machines) and, if necessary, with his suppliers, which requires time and effort due to communication and delivery routes. Hence, an autonomous acting machine or component that deal with needed changes through automatically triggered adaptations would facilitate this process. In this paper, subtasks for constructing autonomous adaptive machines are identified and discussed. The underlying assumption is that changes of machines and components can be supported through configuration technologies because those handle variability and supply automatic derivation methods for computing needed changes in terms of machine and component updates.

Combining Qualitative Spatial Reasoning and Ontological Reasoning for Supporting Robot Tasks.

Abstract: This paper presents an application of spatial and ontology reasoning technologies for mobile robot tasks. We provide a combination of the spatial reasoning calculi RCC-8 and CDC as well as their integration with OWLbased ontologies. An architecture that combines inference tools like Prolog, description logic reasoners, and complex-event processing implements our approach. We illustrate the results with a mobile robot scenario in a restaurant. In this paper, global path-finding demonstrates the use of qualitative spatial and ontological

Thoughts about Structuralization, Specialization, Instantiation, and Metaization.

Abstract: In knowledge engineering, ontology creation, and especially in knowledge-based configuration often used relations are: aggregate relations (has-parts, here called structural relations), specialization relation (is-a), and instantiation (instance-of). A combination of the later is called metaization, which denotes the use of multiple instantiation layers. Structural and specialization relations are mainly used for organizing the knowledge represented on one layer. Instantiation layers model different kind of knowledge, i.e. knowledge about sets, individuals, and knowledge about knowledge (metaknowledge). By applying reasoning techniques on each layer, reasoning on metaknowledge is enabled.

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.

Object Learning Through Active Exploration

Abstract: This paper addresses the problem of active object learning by a humanoid child-like robot, using a developmental approach. We propose a cognitive architecture where the visual representation of the objects is built incrementally through active exploration. We present the design guidelines of the cognitive architecture, its main functionalities, and we outline the cognitive process of the robot by showing how it learns to recognize objects in a human-robot interaction scenario inspired by social parenting. The robot actively explores the objects through manipulation, driven by a combination of social guidance and intrinsic motivation. Besides the robotics and engineering achievements, our experiments replicate some observations about the coupling of vision and manipulation in infants, particularly how they focus on the most informative objects. We discuss the further benefits of our architecture, particularly how it can be improved and used to ground concepts.