Institute for Artificial Intelligence
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Item-typ:Veröffentlichung, An Ontological Model of User Preferences(RWTH Aachen, 2023); ; ; ; The notion of preferences plays an important role in many disciplines including service robotics which is concerned with scenarios in which robots interact with humans. These interactions can be favored by robots taking human preferences into account. This raises the issue of how preferences should be represented to support such preference-aware decision making. Several formal accounts for a notion of preferences exist. However, these approaches fall short on defining the nature and structure of the options that a robot has in a given situation. In this work, we thus investigate a formal model of preferences where options are non-atomic entities that are defined by the complex situations they bring about.Konferenzbeitrag20 28 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Transforming Web Knowledge into Actionable Knowledge Graphs for Robot Manipulation Tasks(RWTH Aachen, 2024); ; ; ; One of the visions in AI based robotics are household robots that can autonomously handle a variety of meal preparation tasks. Based on this scenario, we present a best practice tutorial on how to create actionable knowledge graphs that a robot can use for execution of task variations of cutting actions. We implemented a solution for this task that integrates all necessary software components in the framework of the robot control process. In the context of this tutorial, we focus on knowledge acquisition, knowledge representation and reasoning, and simulating robot action execution, bringing these components together into a learning environment that – in the extended version – introduces the whole control process of Cognitive Robotics. In particular, the Tutorial will detail necessary concepts a knowledge graph should include for robot action execution, how web knowledge can be automatically acquired for the domain of cutting fruits, and how the created knowledge graph can be used to let robots execute tasks like slicing a cucumber or quartering an apple. The learning environment follows an immersive approach, using a physics-based simulation environment for visualization purposes that helps to illustrate the concepts taught in the tutorial.Konferenzbeitrag29 16 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Towards Reactive Robotics with a Pinch of Image-Schematic ReasoningToday’s robots do not possess a deep understanding of interactions between physical objects that is also available to their behavior generation modules and as such show brittle performance in realistic environments. While this suggests a robot would therefore need more knowledge, its decisions should not be too complicated to arrive at or else the robot risks losing track of what matters from its environment. Thus, we investigate a mix of reactive approaches to robotics and reasoning, and propose a simplified theory of typical changes between image schemas. We show how this theory could be integrated in a robot’s perception-action loop, and describe some examples of using this theory to infer actions and perception queries for various stages of a pouring task. We are integrating this inference procedure into a simulated robot, but this integration is yet to be completed and as such, future work.Konferenzbeitrag34 16 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Between Input and Output: The Importance of Modelling Transients in Meal Preparation TasksWe are moving closer to autonomous robots preparing meals. While restaurant robots in static environments already are successfully performing single actions like making pizza, the goal is to enablerobots to perform changing actions, in various environments and with any available object. Towards this goal, a methodology for creating actionable knowledge graphs that can be used to parameterise general action plans has been proposed. However, for extended failure handling towards fully automated action execution, we argue that transients need to be considered. A transient can be described as a transitory object in a task that is not the same as the input object anymore but not yet the output object of the task. For example, when pouring ingredients into a bowl to make the dough, the added ingredients form a mass of ingredients (here: a transient) that only becomes dough through mixing them. This work shows how transients can be modelled and how robots can integrate and possibly benefit from this modelling.Konferenzbeitrag43 16 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Perception for imagination-enabled robots(2025-10-14); ; ; Recent advancements in robotics and computer vision have enhanced object recognition and control strategies. However, these developments do not fully tackle the challenges of autonomous manipulation in dynamic, unstructured environments like households. Current systems often rely on specialized algorithms for perception, which lack generalizability and fail to verify the plausibility of their results. This thesis proposes a comprehensive framework that enhances robotic perception and manipulation in dynamic, unstructured environments by integrating a photorealistic, physics-enabled game engine. The core contributions of this research are threefold. First, it presents a unified perception architecture that combines imagistic reasoning, process-level control, and perception task adaptation within a single system. This architecture enables robots to construct internal hypotheses, simulate expected sensor data, and verify perceptual results against rendered scenes, facilitating grounded and introspective perception in real-world tasks. Second, the thesis presents a game-engine-based belief representation, utilizing real-time simulation as an internal model of belief states to enable high-fidelity visual hypothesis generation. The simulated environment represents a dynamic world model, including the robot state, allowing the system to assess the plausibility of perceptual results and predict the visual consequences of actions. Lastly, Perception Pipeline Trees (PPTs) are introduced as a modular process model for adaptive perception execution. PPTs combine hierarchical execution with flexible control flow, supporting reactive switching, concurrent processing, and introspective verification. This model accommodates conventional vision tasks and imagistic reasoning processes within a unified representation. The framework demonstrates effectiveness in real-world applications, including household assistance scenarios where robots perform tasks such as recognizing and manipulating objects, as well as tracking and interacting with humans. By enabling robots to not only observe but also reason about their environment through simulation, this work advances task adaptability, perception accuracy, and reasoning capability, laying the foundation for the next generation of intelligent, imagination-enabled robots.Dissertation77 62 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Prospective perception through cognitive emulation for robot manipulation tasks: "Perceiving like humans do"(2025-10-07); ; 104 67 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, A Plan Executive Architecture for Transferable Robot Behavior: Generalized Action Plans and Their Context-Adaptive Execution in Real-World Settings(2025-10-02); ; 39 50 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Towards a Knowledge Engineering Methodology for Flexible Robot Manipulation in Everyday Tasks(RWTH Aachen, 2024); ; ; ; In the last decade, there have been great advancements in household robotics, enabling robots to autonomously accomplish household tasks. These robots are typically programmed for specific tasks and/ or objects. We hypothesise that the lack of flexibility in fulfilling new ad-hoc task requests can be overcome by a knowledge-based approach, allowing robots to infer how to address a new task or carry out known tasks on new objects. Towards this goal, we propose a knowledge-based methodology that leverages knowledge already existing on the web to construct an ontology supporting robots in reasoning about parameters that influence manipulation actions for execution of task variations on a range of objects. The ontology comprises object and action information, covering dispositions and affordances as well as task-specific properties. As a proof-of-concept, we manually construct a food-cutting ontology by importing and linking knowledge from relevant ontologies in addition to extracting and semantically enhancing knowledge from unstructured web sources. We demonstrate how robots can query the ontology and translate the contained information into action parameters. We evaluate the feasibility of the created ontology by simulating a robot accessing the ontology for parameterisation of actions to perform task variations of cutting.text::conference output::conference proceedings::conference paper30 14 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, ProductKG: A Product Knowledge Graph for User Assistance in Daily ActivitiesThe Web offers plenty of product information that is valuable for supporting decision processes. Research on Web knowledge acquisition and the Semantic Web has led to the creation of many domain ontologies and Web applications. What still is lacking is a connection of such knowledge to the real world. If object information is linked to environment information, users can get better, more personalised support in their daily activities like shopping or cooking since this enables them to link information about leftover products in the fridge to recipe information or a health profile to products the user is looking at in the store. It has been shown that semantic Digital Twins can successfully link object to environment information that can be used by agents like smartphone or service robot. Such semantic Digital Twins can offer even more services to users if they are connected to product information from the Web. This work introduces ProductKG, an open-source product knowledge graph integrating modular product information from the Web as well as accurate environment information from a semantic Digital Twin that can be customised for different applications and used devices as an example knowledge graph for assisting users in daily activities. We describe the design process and modularity of the knowledge graph as well as example applications of it, including an Augmented Reality shopping assistant, a dietary recommender and a hands-free recipe application. The modular ontologies enable personalisation of applications as well as accessing object information in relation to the current environment. We evaluate the acceptance of one example application through a user study. ProductKG is publicly available and will be maintained and extended over time in order to facilitate various applications such as in the retail and household domainKonferenzbeitrag12 30 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Inferring dispositions from object shape and material with physics game engine modellingDispositional qualities are the characteristics of an object that are attributed to it’s properties, such as mass, color, shape, material, etc. Understanding how the design of an object affords such qualities is a crucial task in robotics. Such as a cup being functionally designed to hold or contain something, and structurally designed to be carried or grasped by its handle. Dispositions tend to be more independent of an environment than affordances, since they are related to fundamental characteristics of an object. Whereas, affordances define the action possibilities with the object in the given environment with an agent capable of manipulating them, such as a bottle of water affords drinking possibility to an adult but it is hard for an infant to open the bottle cap in order to drink from it. The topic of affordances is widely explored in the domain of robotics where it plays a vital role for basic object manipulation skills. In this paper, we present an approach for disposition learning about an object from it’s shape and material information provided by a physics engine. We postulate our hypothesis around the current state of the art game engines which have complex object rendering and modelling techniques. The modelling of shape and material information about the object can be harvested as a source of knowledge for the given object in the environment. An intelligent agent thus benefits from having prior information about such objects in the world.Konferenzbeitrag15 15