Knowledge-based execution configuration for adaptive behavior trees
Automated planning is commonly used to obtain plans to solve particular tasks. To execute these plans, Behavior Trees have emerged as a popular execution architecture due to their reactivity and modularity. Configuring the execution of a plan into a Behavior Tree requires expanding the high level ac...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:upcommonspor::b32c469e373661ecfda7fb65687cfed4 |
| Acceso en línea: | https://hdl.handle.net/2117/460387 https://dx.doi.org/10.1007/s10846-026-02373-1 |
| Access Level: | acceso abierto |
| Palabra clave: | Robotic manipulation Behavior trees Automated planning Knowledge representation and reasoning Ontologies Àrees temàtiques de la UPC::Informàtica::Robòtica |
| Sumario: | Automated planning is commonly used to obtain plans to solve particular tasks. To execute these plans, Behavior Trees have emerged as a popular execution architecture due to their reactivity and modularity. Configuring the execution of a plan into a Behavior Tree requires expanding the high level actions into the proper Behavior Tree structure. Typically, this is achieved using of pre-defined rigid templates. In this work, we propose a novel approach to generating the Behavior Trees using ontologies. The generated Behavior Trees are tailored to the specific requirements of a task and the world by using modifiers to a base template that provides a general solution to the task. These modifiers and their properties are formally defined using ontologies. A proof of concept is developed, illustrating how the Behavior Trees for the execution of manipulation tasks in a kitchen scenario can be adapted to varying conditions by applying different modifiers. |
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