مورد إلكتروني
Morphological symmetries in robot learning
| العنوان: | Morphological symmetries in robot learning |
|---|---|
| بيانات النشر: | OpenReview.net 2023 |
| تفاصيل مُضافة: | Universitat Politècnica de Catalunya. Departament de Ciències de la Computació Universitat Politècnica de Catalunya. Institut de Robòtica i Informàtica Industrial, CSIC-UPC Barcelona Supercomputing Center Universitat Politècnica de Catalunya. IDEAI-UPC - Intelligent Data sciEnce and Artificial Intelligence Research Group Universitat Politècnica de Catalunya. ROBiri - Grup de Percepció i Manipulació Robotitzada de l'IRI Ordoñez Apraez, Daniel Felipe Martín Muñoz, Mario Agudo Martínez, Antonio Moreno-Noguer, Francesc |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | This work studies the impact of morphological symmetries in learning applications in robotics. Morphological symmetries are a predominant feature in both biological and robotic systems, arising from the presence of planes/axis of symmetry in the system's morphology. This results in harmonious duplication and distribution of body parts (e.g., humans' sagittal/left-right symmetry). Morphological symmetries become a significant learning prior as they extend to symmetries in the system's dynamics, optimal control policies, and in all proprioceptive and exteroceptive measurements, related to the system's dynamics evolution \cite{ordonez2023discrete}. Exploiting these symmetries in learning applications offers several advantageous outcomes, such as the use of data augmentation to mitigate the cost and challenges of data collection, or the use of equivariant/invariant function approximation models (e.g., neural networks) to improve sample efficiency and generalization, while reducing the number of trainable parameters. Lastly, we provide a video presentation and an open access repository reproducing our experiments and allowing for rapid prototyping in robot learning applications exploiting morphological symmetries. This work is supported by the Spanish government with the project MoHuCo PID2020-120049RB-I00 and the ERA-Net Chistera project IPALM PCI2019-103386. Peer Reviewed Postprint (published version) |
| مصطلحات الفهرس: | Àrees temàtiques de la UPC::Informàtica::Robòtica, Machine learning, Robots, Symmetry (Biology), Morphological symmetries, Finite symmetry groups, Locomotion, Symmetric dynamical systems, Symmetric robotic systems, Symmetries in robotics, Aprenentatge automàtic, Simetria (Biologia), Conference report |
| URL: | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-120049RB-I00/ES/MODELIZACION DE HUMANOS EN EL CONTEXTO info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PCI2019-103386/ES/PERCEPCION-ACCION-APRENDIZAJE INTERACTIVO PARA MODELAR OBJETOS |
| الإتاحة: | Open access content. Open access content Open Access |
| ملاحظة: | application/pdf English |
| أرقام أخرى: | HGF oai:upcommons.upc.edu:2117/390412 Ordoñez, D. [et al.]. Morphological symmetries in robot learning. A: Workshop Symmetry - RSS Workshop on Symmetries in Robot Learning. "RSS 2023 Workshop on Symmetries in Robot Learning, RSS 2023 Workshop Symmetry: Daegu, Republic of Korea, Jul. 10 2023". OpenReview.net, 2023. 1390668996 |
| المصدر المساهم: | UNIV POLITECNICA DE CATALUNYA From OAIster®, provided by the OCLC Cooperative. |
| رقم الأكسشن: | edsoai.on1390668996 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |