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PerSim: Perception for Planetary Prospection and Internal Simulation

Raúl Domínguez; Mariela De Lucas Alvarez; Siddhant Kadwe; Christoph Hertzberg; Siddhant Shete; Leon Cedric Danter; Marko Jankovik; Shubham Vyas; Jonas Eisenmenger; Pierre Willenbrock; André Felmet; Vikram Unnithan; Frank Kirchner
In: 17th Symposium on Advanced Space Technologies in Robotics and Automation. ESA/Estec Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA-2023), October 18-20, Leiden, Netherlands, ASTRA Proceedings, Noordwijk The Netherlands, 2023.


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 on- board 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.


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