Hassouna, Vanessa
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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 15 - Some of the metrics are blocked by yourconsent settings
Item-typ:Veröffentlichung, Steps Towards Generalized Manipulation Action Plans - Tackling Mixing TaskIn the rapidly evolving field of household robotics, the ability to autonomously execute complex tasks like "Serve Me Breakfast" introduces considerable technical challenges, particularly in the precise and adaptive handling of mixing tasks that involve substances with diverse densities and viscosities. This study advances the field of cognitive robotics by delving into the intricacies of everyday, complex, and highly variable activities within household settings. These scenarios demand that robots manage multiple, interconnected actions—a concept known as schemas. We present a holistic strategy to enhance household robots with sophisticated task execution capabilities, utilizing the Cognitive Robotic Abstract Machine (CRAM) framework for strategic planning and execution. Our method begins with an in-depth analysis of human behaviour to develop a theoretical model that guides the creation of adaptable and comprehensible action plans for robots. A crucial element of our approach involves using Narrative Enabled Episodic Memories (NEEMs), which capture detailed records of task executions to aid performance analysis and experiential learning. We propose incorporating additional criteria based on events recorded in the NEEMs to assess task success. For instance, a robot maintaining a steady grip on the whisk while interacting with a fluid suggests correctly executing mixing tasks. These criteria enable further evaluation of performance through simulations, despite potential limitations in simulation fidelity. This article explores the transition from human expertise to robotic execution of mixing tasks in household environments, the methodology for gathering and analysing NEEMs, and their prospective future applications.Konferenzbeitrag28 14 - 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