PerSim: Perception for Planetary Prospection and Internal Simulation

التفاصيل البيبلوغرافية
العنوان: PerSim: Perception for Planetary Prospection and Internal Simulation
المؤلفون: Domínguez, Raúl, De Lucas Alvarez, Mariela, Kadwe, Siddhant, Shette, Siddhant, Herztberg, Christoph, Cedric Danter, Leon, Jankovik, Marko, Vyas, Shubham, Eisenmenger, Jonas, Willenbrock, Pierre, Felmet, André, Unnithan, Vikram, Kirchner, Frank
المصدر: ASTRA, 17th Symposium on Advanced Space Technologies in Robotics and Automation, Scheltema, Leiden, Netherlands, 18.-20.10.2023
بيانات النشر: European Space Agency (ESA)
سنة النشر: 2023
المجموعة: Zenodo
الوصف: For planetary robotics autonomous prospecting, robust, long-term navigation becomes crucial. The goal of the research project PerSim is to develop technology to address some of the challenges of active perception for resource identification and long-term navigation strategies in an integrated architecture. The fist assessment addressed autonomous selection of regions for inspection, combined arm-base approach, close range data acquisition and categorization of the acquired spectral data using Deep Learning. Furthermore, autonomous navigation including potential failure prediction and avoidance are also scoped. The following targets are pursued in the second assessment: an internal simulation to enhance the system safety and provide means for autonomous onboard safe testing, an episodic memory representation to serve as basis for the implementation of long term adaptation and finally a repertoire of behaviors to enable different motion modalities. The paper provides insights on the approaches and initial results.
نوع الوثيقة: conference object
اللغة: unknown
Relation: https://doi.org/10.5281/zenodo.10634583; https://doi.org/10.5281/zenodo.10634584; oai:zenodo.org:10634584
DOI: 10.5281/zenodo.10634584
الاتاحة: https://doi.org/10.5281/zenodo.10634584
Rights: info:eu-repo/semantics/openAccess ; Creative Commons Attribution 4.0 International ; https://creativecommons.org/licenses/by/4.0/legalcode
رقم الانضمام: edsbas.82380D34
قاعدة البيانات: BASE