Range-dependent Terrain Mapping and Multipath Planning using Cylindrical Coordinates for a Planetary Exploration Rover
This paper presents terrain mapping and path‐planning techniques that are key issues for autonomous mobility of a planetary exploration rover. In this work, a LIDAR (light detection and ranging) sensor is used to obtain geometric information on the terrain. A point cloud of the terrain feature provi...
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| Published in | Journal of field robotics Vol. 30; no. 4; pp. 536 - 551 |
|---|---|
| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
Hoboken
Blackwell Publishing Ltd
01.07.2013
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1556-4959 1556-4967 1556-4967 |
| DOI | 10.1002/rob.21462 |
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| Abstract | This paper presents terrain mapping and path‐planning techniques that are key issues for autonomous mobility of a planetary exploration rover. In this work, a LIDAR (light detection and ranging) sensor is used to obtain geometric information on the terrain. A point cloud of the terrain feature provided from the LIDAR sensor is usually converted to a digital elevation map. A sector‐shaped reference grid for the conversion process is proposed in this paper, resulting in an elevation map with cylindrical coordinates termed as C2DEM. This conversion approach achieves a range‐dependent resolution for the terrain mapping: a detailed terrain representation near the rover and a sparse representation far from the rover. The path planning utilizes a cost function composed of terrain inclination, terrain roughness, and path length indices, each of which is subject to a weighting factor. The multipath planning developed in this paper first explores possible sets of weighting factors and generates multiple candidate paths. The most feasible path is then determined by a comparative evaluation between the candidate paths. Field experiments with a rover prototype at a Lunar/Martian analog site were performed to confirm the feasibility of the proposed techniques, including the range‐dependent terrain mapping with C2DEM and the multipath‐planning method. |
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| AbstractList | This paper presents terrain mapping and path‐planning techniques that are key issues for autonomous mobility of a planetary exploration rover. In this work, a LIDAR (light detection and ranging) sensor is used to obtain geometric information on the terrain. A point cloud of the terrain feature provided from the LIDAR sensor is usually converted to a digital elevation map. A sector‐shaped reference grid for the conversion process is proposed in this paper, resulting in an elevation map with cylindrical coordinates termed as C
2
DEM. This conversion approach achieves a range‐dependent resolution for the terrain mapping: a detailed terrain representation near the rover and a sparse representation far from the rover. The path planning utilizes a cost function composed of terrain inclination, terrain roughness, and path length indices, each of which is subject to a weighting factor. The multipath planning developed in this paper first explores possible sets of weighting factors and generates multiple candidate paths. The most feasible path is then determined by a comparative evaluation between the candidate paths. Field experiments with a rover prototype at a Lunar/Martian analog site were performed to confirm the feasibility of the proposed techniques, including the range‐dependent terrain mapping with C
2
DEM and the multipath‐planning method. This paper presents terrain mapping and path‐planning techniques that are key issues for autonomous mobility of a planetary exploration rover. In this work, a LIDAR (light detection and ranging) sensor is used to obtain geometric information on the terrain. A point cloud of the terrain feature provided from the LIDAR sensor is usually converted to a digital elevation map. A sector‐shaped reference grid for the conversion process is proposed in this paper, resulting in an elevation map with cylindrical coordinates termed as C2DEM. This conversion approach achieves a range‐dependent resolution for the terrain mapping: a detailed terrain representation near the rover and a sparse representation far from the rover. The path planning utilizes a cost function composed of terrain inclination, terrain roughness, and path length indices, each of which is subject to a weighting factor. The multipath planning developed in this paper first explores possible sets of weighting factors and generates multiple candidate paths. The most feasible path is then determined by a comparative evaluation between the candidate paths. Field experiments with a rover prototype at a Lunar/Martian analog site were performed to confirm the feasibility of the proposed techniques, including the range‐dependent terrain mapping with C2DEM and the multipath‐planning method. This paper presents terrain mapping and path-planning techniques that are key issues for autonomous mobility of a planetary exploration rover. In this work, a LIDAR (light detection and ranging) sensor is used to obtain geometric information on the terrain. A point cloud of the terrain feature provided from the LIDAR sensor is usually converted to a digital elevation map. A sector-shaped reference grid for the conversion process is proposed in this paper, resulting in an elevation map with cylindrical coordinates termed as C super(2)DEM. This conversion approach achieves a range-dependent resolution for the terrain mapping: a detailed terrain representation near the rover and a sparse representation far from the rover. The path planning utilizes a cost function composed of terrain inclination, terrain roughness, and path length indices, each of which is subject to a weighting factor. The multipath planning developed in this paper first explores possible sets of weighting factors and generates multiple candidate paths. The most feasible path is then determined by a comparative evaluation between the candidate paths. Field experiments with a rover prototype at a Lunar/Martian analog site were performed to confirm the feasibility of the proposed techniques, including the range-dependent terrain mapping with C super(2)DEM and the multipath-planning method. This paper presents terrain mapping and path-planning techniques that are key issues for autonomous mobility of a planetary exploration rover. In this work, a LIDAR (light detection and ranging) sensor is used to obtain geometric information on the terrain. A point cloud of the terrain feature provided from the LIDAR sensor is usually converted to a digital elevation map. A sector-shaped reference grid for the conversion process is proposed in this paper, resulting in an elevation map with cylindrical coordinates termed as C2DEM. This conversion approach achieves a range-dependent resolution for the terrain mapping: a detailed terrain representation near the rover and a sparse representation far from the rover. The path planning utilizes a cost function composed of terrain inclination, terrain roughness, and path length indices, each of which is subject to a weighting factor. The multipath planning developed in this paper first explores possible sets of weighting factors and generates multiple candidate paths. The most feasible path is then determined by a comparative evaluation between the candidate paths. Field experiments with a rover prototype at a Lunar/Martian analog site were performed to confirm the feasibility of the proposed techniques, including the range-dependent terrain mapping with C2DEM and the multipath-planning method. [PUBLICATION ABSTRACT] |
| Author | Kubota, Takashi Ishigami, Genya Otsuki, Masatsugu |
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| Cites_doi | 10.1109/ROBOT.1994.351061 10.1002/rob.20184 10.1109/IROS.2008.4651203 10.1109/AERO.2007.352683 10.1177/02783640122067453 10.1007/BF00126401 10.1007/978-3-642-13408-1_19 10.1109/CRV.2007.63 10.1109/MRA.2004.1371614 10.1016/S1474-6670(17)33395-5 10.1007/b94718 10.1109/70.508439 10.1002/rob.20287 10.1007/978-3-642-32060-6_42 10.1007/978-3-642-13408-1_44 10.1016/S0921-8890(03)00004-6 10.1007/s11263-007-0046-z 10.1016/j.robot.2011.03.004 10.14358/PERS.70.1.77 10.1109/ROBOT.2009.5152504 10.1109/ROBOT.2008.4543184 10.14358/PERS.71.10.1129 10.1002/rob.20109 10.1177/02783649922066493 10.1109/IROS.2006.282358 10.1117/12.486764 10.1109/21.148426 10.1109/AERO.2002.1035370 10.1007/978-3-642-03991-1 10.1016/j.pss.2009.09.021 10.4271/972487 |
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| References | Carsten, J., Rankin, A., Ferguson, D., & Stentz, A. (2008). Global planning on the Mars exploration rovers: Software integration and surface testing. Journal of Field Robotics, 26, 337-357. Rekleitis, I., Bedwani, J.-L., Dupuis, E., Lamarche, T., & Allard, P. (2012). Autonomous over-the-horizon navigation using Lidar data. Autonomous Robots. Buehler, M., Iagnemma, K., & Singh, S., editors (2005). The 2005 DARPA Grand Challenge: The Great Robot Race, Springer Tracts in Advanced Robotics (STAR) Series, Vol. 36. Berlin, Heidelberg: Springer-Verlag. Thrun, S., Thayer, S., Whittaker, W., Baker, C., Burgard, W., Ferguson, D., Hahnel, D., Montemerlo, M., Morris, A., Omohundro, Z., Reverte, C., & Whittaker, W. (2004). Autonomous exploration and mapping of abandoned mines. IEEE Robotics & Automation Magazine, 11, 79-91. Matthies, L., Maimone, M., Johnson, A., Cheng, Y., Willson, R., Villalpando, C., Goldberg, S., & Huertas, A. (2007). Computer vision on Mars. International Journal of Computer Vision. Barraquand, J., Langlois, B., & Latombe, J. (1992). Numerical potential field techniques for robot path planning. IEEE Transaction on Systems, Man and Cybernetics, 22, 224-241. Iagnemma, K., & Dubowsky, S. (2004). Mobile robots in rough terrain: Estimation, motion planning, and control with application to planetary rovers. Berlin, Heidelberg: Springer-Verlag. Volpe, R. (1999). Navigation results from desert field tests of the Rocky 7 Mars rover prototype. The International Journal of Robotics Research, 18(7), 669-683. Barfoot, T., Furgale, P., Stenning, B., Carle, P., Thomson, L., Osinski, G., Daly, M., & Ghafoor, N. (2011). Field testing of a rover guidance, navigation, and control architecture to support a ground-ice prospecting mission to mars. Robotics and Autonomous Systems, 59, 472-488. Li, R., Di, K., Matthies, L., Arvidson, R., Folkner, W., & Archinal, B. (2004). Rover localization and landing site mapping technology for the 2003 Mars exploration rover mission. Journal of Photogrammetric Engineering and Remote Sensing, 70, 77-90. Buehler, M., Iagnemma, K., & Singh, S., editors (2009). The DARPA Urban Challenge: Autonomous Vehicles in City Traffic, Springer Tracts in Advanced Robotics (STAR) Series, Vol. 56. Berlin, Heidelberg: Springer-Verlag. Ferguson, D., & Stentz, A. (2006). Using interpolation to improve path planning: The field d* algorithm. Journal of Field Robotics, 23, 79-101. Maimone, M., Cheng, Y., & Matthies, L. (2007). Two years of visual odometry on the Mars exploration rovers. Journal of Field Robotics, 24. Matthies, L. (1992). Stereo vision for planetary rovers: Stochastic modeling to near real-time implementation. International Journal of Computer Vision, 8, 71-91. Kavraki, L. E., Svestka, P., Latombe, J.-C., & Overmars, M. H. (1996). Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transaction on Robotics and Automation, 12, 566-580. Olson, C., Matthies, L., & Schoppers, M. (2003). Rover navigation using stereo ego-motion. Robotics and Autonomous Systems, 43, 215-229. Barfoot, T., Furgale, P., Osinski, G., Ghafoor, N., & Williams, K. (2010). Field testing of robotic technologies to support ground ice prospecting in martian polygonal terrain. Planetary and Space Science, 58, 671-681. Li, R., Squyres, S., Arvidson, R., Archinal, B., Bell, J., Cheng, Y., Crumpler, L., Marais, D. D., Di, K., Ely, T., Golombek, M., Graat, E., Grant, J., Guinn, J., Johnson, A., Greeley, R., Kirk, R., Maimone, M., Matthies, L., Malin, M., Parker, T., Sims, M., Soderblom, L., Thompson, S., Wang, J., Whelley, P., & Xu, F. (2005). Initial results of rover localization and topographic mapping for the 2003 Mars exploration rover mission. Journal of Photogrammetric Engineering & Remote Sensing (Special Issue on Mapping Mars), 71, 1129-1142. LaValle, S. M., & Kuffner, J. J. (2001). Randomized kinodynamic planning. International Journal of Robotics Research, 20. 2010; 58 2012 2011 1998 2009 2008 1997 2007 2006 1995 2005 1994 2004 2011; 59 2003 2002 1996; 12 2001; 20 2009; 56 2004; 11 1992; 8 2004; 70 2006; 23 2000 1999; 18 2008; 26 2005; 71 2013 1992; 22 2007; 24 2003; 43 2005; 36 Buehler M. (e_1_2_8_6_1) 2005 e_1_2_8_28_1 e_1_2_8_24_1 e_1_2_8_47_1 e_1_2_8_26_1 e_1_2_8_49_1 Rekleitis I. (e_1_2_8_36_1) 2012 e_1_2_8_3_1 e_1_2_8_7_1 e_1_2_8_9_1 e_1_2_8_20_1 e_1_2_8_43_1 Biesiadecki J. (e_1_2_8_5_1) 2006 e_1_2_8_22_1 e_1_2_8_45_1 e_1_2_8_41_1 e_1_2_8_17_1 e_1_2_8_19_1 e_1_2_8_13_1 e_1_2_8_15_1 e_1_2_8_38_1 Iagnemma K. (e_1_2_8_16_1) 2004 e_1_2_8_32_1 e_1_2_8_11_1 e_1_2_8_34_1 e_1_2_8_51_1 e_1_2_8_30_1 e_1_2_8_29_1 e_1_2_8_25_1 e_1_2_8_46_1 e_1_2_8_27_1 e_1_2_8_48_1 e_1_2_8_2_1 e_1_2_8_4_1 e_1_2_8_8_1 e_1_2_8_21_1 e_1_2_8_42_1 e_1_2_8_23_1 e_1_2_8_44_1 e_1_2_8_40_1 e_1_2_8_18_1 e_1_2_8_39_1 e_1_2_8_14_1 e_1_2_8_35_1 e_1_2_8_37_1 e_1_2_8_10_1 e_1_2_8_31_1 e_1_2_8_12_1 e_1_2_8_33_1 e_1_2_8_52_1 e_1_2_8_50_1 |
| References_xml | – reference: Buehler, M., Iagnemma, K., & Singh, S., editors (2009). The DARPA Urban Challenge: Autonomous Vehicles in City Traffic, Springer Tracts in Advanced Robotics (STAR) Series, Vol. 56. Berlin, Heidelberg: Springer-Verlag. – reference: Maimone, M., Cheng, Y., & Matthies, L. (2007). Two years of visual odometry on the Mars exploration rovers. Journal of Field Robotics, 24. – reference: Matthies, L. (1992). Stereo vision for planetary rovers: Stochastic modeling to near real-time implementation. International Journal of Computer Vision, 8, 71-91. – reference: Kavraki, L. E., Svestka, P., Latombe, J.-C., & Overmars, M. H. (1996). Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transaction on Robotics and Automation, 12, 566-580. – reference: Rekleitis, I., Bedwani, J.-L., Dupuis, E., Lamarche, T., & Allard, P. (2012). Autonomous over-the-horizon navigation using Lidar data. Autonomous Robots. – reference: Barfoot, T., Furgale, P., Osinski, G., Ghafoor, N., & Williams, K. (2010). Field testing of robotic technologies to support ground ice prospecting in martian polygonal terrain. Planetary and Space Science, 58, 671-681. – reference: Barfoot, T., Furgale, P., Stenning, B., Carle, P., Thomson, L., Osinski, G., Daly, M., & Ghafoor, N. (2011). Field testing of a rover guidance, navigation, and control architecture to support a ground-ice prospecting mission to mars. Robotics and Autonomous Systems, 59, 472-488. – reference: Thrun, S., Thayer, S., Whittaker, W., Baker, C., Burgard, W., Ferguson, D., Hahnel, D., Montemerlo, M., Morris, A., Omohundro, Z., Reverte, C., & Whittaker, W. (2004). Autonomous exploration and mapping of abandoned mines. IEEE Robotics & Automation Magazine, 11, 79-91. – reference: Li, R., Squyres, S., Arvidson, R., Archinal, B., Bell, J., Cheng, Y., Crumpler, L., Marais, D. D., Di, K., Ely, T., Golombek, M., Graat, E., Grant, J., Guinn, J., Johnson, A., Greeley, R., Kirk, R., Maimone, M., Matthies, L., Malin, M., Parker, T., Sims, M., Soderblom, L., Thompson, S., Wang, J., Whelley, P., & Xu, F. (2005). Initial results of rover localization and topographic mapping for the 2003 Mars exploration rover mission. Journal of Photogrammetric Engineering & Remote Sensing (Special Issue on Mapping Mars), 71, 1129-1142. – reference: LaValle, S. M., & Kuffner, J. J. (2001). Randomized kinodynamic planning. International Journal of Robotics Research, 20. – reference: Barraquand, J., Langlois, B., & Latombe, J. (1992). Numerical potential field techniques for robot path planning. IEEE Transaction on Systems, Man and Cybernetics, 22, 224-241. – reference: Iagnemma, K., & Dubowsky, S. (2004). Mobile robots in rough terrain: Estimation, motion planning, and control with application to planetary rovers. Berlin, Heidelberg: Springer-Verlag. – reference: Volpe, R. (1999). Navigation results from desert field tests of the Rocky 7 Mars rover prototype. The International Journal of Robotics Research, 18(7), 669-683. – reference: Olson, C., Matthies, L., & Schoppers, M. (2003). Rover navigation using stereo ego-motion. Robotics and Autonomous Systems, 43, 215-229. – reference: Li, R., Di, K., Matthies, L., Arvidson, R., Folkner, W., & Archinal, B. (2004). Rover localization and landing site mapping technology for the 2003 Mars exploration rover mission. Journal of Photogrammetric Engineering and Remote Sensing, 70, 77-90. – reference: Ferguson, D., & Stentz, A. (2006). Using interpolation to improve path planning: The field d* algorithm. Journal of Field Robotics, 23, 79-101. – reference: Matthies, L., Maimone, M., Johnson, A., Cheng, Y., Willson, R., Villalpando, C., Goldberg, S., & Huertas, A. (2007). Computer vision on Mars. International Journal of Computer Vision. – reference: Buehler, M., Iagnemma, K., & Singh, S., editors (2005). The 2005 DARPA Grand Challenge: The Great Robot Race, Springer Tracts in Advanced Robotics (STAR) Series, Vol. 36. Berlin, Heidelberg: Springer-Verlag. – reference: Carsten, J., Rankin, A., Ferguson, D., & Stentz, A. (2008). Global planning on the Mars exploration rovers: Software integration and surface testing. 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| SubjectTerms | Cylindrical coordinates Elevation Lidar Representations Sensors Studies Terrain Terrain mapping Weighting |
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| Title | Range-dependent Terrain Mapping and Multipath Planning using Cylindrical Coordinates for a Planetary Exploration Rover |
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