caa a22 4500 606245103 CHVBK 20210128101333.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s12567-014-0072-y doi (NATIONALLICENCE)springer-10.1007/s12567-014-0072-y Data fusion strategies for hazard detection and safe site selection for planetary and small body landings [Elektronische Daten] [F. Câmara, J. Oliveira, T. Hormigo, J. Araújo, R. Ribeiro, A. Falcão, M. Gomes, O. Dubois-Matra, S. Vijendran] This paper discusses the design and evaluation of data fusion strategies to perform tiered fusion of several heterogeneous sensors and a priori data. The aim is to increase robustness and performance of hazard detection and avoidance systems, while enabling safe planetary and small body landings anytime, anywhere. The focus is on Mars and asteroid landing mission scenarios and three distinct data fusion algorithms are introduced and compared. The first algorithm consists of a hybrid camera-LIDAR hazard detection and avoidance system, the H2DAS, in which data fusion is performed at both sensor-level data (reconstruction of the point cloud obtained with a scanning LIDAR using the navigation motion states and correcting the image for motion compensation using IMU data), feature-level data (concatenation of multiple digital elevation maps, obtained from consecutive LIDAR images, to achieve higher accuracy and resolution maps while enabling relative positioning) as well as decision-level data (fusing hazard maps from multiple sensors onto a single image space, with a single grid orientation and spacing). The second method presented is a hybrid reasoning fusion, the HRF, in which innovative algorithms replace the decision-level functions of the previous method, by combining three different reasoning engines—a fuzzy reasoning engine, a probabilistic reasoning engine and an evidential reasoning engine—to produce safety maps. Finally, the third method presented is called Intelligent Planetary Site Selection, the IPSIS, an innovative multi-criteria, dynamic decision-level data fusion algorithm that takes into account historical information for the selection of landing sites and a piloting function with a non-exhaustive landing site search capability, i.e., capable of finding local optima by searching a reduced set of global maps. All the discussed data fusion strategies and algorithms have been integrated, verified and validated in a closed-loop simulation environment. Monte Carlo simulation campaigns were performed for the algorithms performance assessment and benchmarking. The simulations results comprise the landing phases of Mars and Phobos landing mission scenarios. CEAS, 2015 Sensor data fusion nationallicence Multi-sensor information fusion nationallicence Fuzzy reasoning nationallicence Probabilistic reasoning nationallicence Evidential reasoning nationallicence Hazard detection and avoidance nationallicence Safe planetary landing nationallicence Câmara F. Spin.Works S.A., Rua Rodrigues Sampaio nº97, 4º, 1150-279, Lisbon, Portugal aut Oliveira J. Spin.Works S.A., Rua Rodrigues Sampaio nº97, 4º, 1150-279, Lisbon, Portugal aut Hormigo T. Spin.Works S.A., Rua Rodrigues Sampaio nº97, 4º, 1150-279, Lisbon, Portugal aut Araújo J. Spin.Works S.A., Rua Rodrigues Sampaio nº97, 4º, 1150-279, Lisbon, Portugal aut Ribeiro R. UNINOVA, Campus da FCT/UNL, 2829-516, Monte de Caparica, Portugal aut Falcão A. UNINOVA, Campus da FCT/UNL, 2829-516, Monte de Caparica, Portugal aut Gomes M. UNINOVA, Campus da FCT/UNL, 2829-516, Monte de Caparica, Portugal aut Dubois-Matra O. ESA-ESTEC, Postbus 299, 2200 AG, Noordwijk, The Netherlands aut Vijendran S. ESA-ESTEC, Postbus 299, 2200 AG, Noordwijk, The Netherlands aut CEAS Space Journal Springer Vienna 7/2(2015-06-01), 271-290 1868-2502 7:2<271 2015 7 12567 https://doi.org/10.1007/s12567-014-0072-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s12567-014-0072-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Câmara F. Spin.Works S.A., Rua Rodrigues Sampaio nº97, 4º, 1150-279, Lisbon, Portugal aut NATIONALLICENCE 700 1- Oliveira J. Spin.Works S.A., Rua Rodrigues Sampaio nº97, 4º, 1150-279, Lisbon, Portugal aut NATIONALLICENCE 700 1- Hormigo T. Spin.Works S.A., Rua Rodrigues Sampaio nº97, 4º, 1150-279, Lisbon, Portugal aut NATIONALLICENCE 700 1- Araújo J. Spin.Works S.A., Rua Rodrigues Sampaio nº97, 4º, 1150-279, Lisbon, Portugal aut NATIONALLICENCE 700 1- Ribeiro R. UNINOVA, Campus da FCT/UNL, 2829-516, Monte de Caparica, Portugal aut NATIONALLICENCE 700 1- Falcão A. UNINOVA, Campus da FCT/UNL, 2829-516, Monte de Caparica, Portugal aut NATIONALLICENCE 700 1- Gomes M. UNINOVA, Campus da FCT/UNL, 2829-516, Monte de Caparica, Portugal aut NATIONALLICENCE 700 1- Dubois-Matra O. ESA-ESTEC, Postbus 299, 2200 AG, Noordwijk, The Netherlands aut NATIONALLICENCE 700 1- Vijendran S. ESA-ESTEC, Postbus 299, 2200 AG, Noordwijk, The Netherlands aut NATIONALLICENCE 773 0- CEAS Space Journal Springer Vienna 7/2(2015-06-01), 271-290 1868-2502 7:2<271 2015 7 12567