火星软着陆障碍检测与规避技术及其仿真演示平台研究
|
摘要
随着人类对火星探测的不断深入,将会促使越来越多的具有更高科考价值的复杂地形进入探测范围,这就对着陆器的安全软着陆提出了更高的技术要求,具有高度的障碍检测能力和障碍规避能力的软着陆自主导航技术已经成为未来火星探测的重要前瞻性技术之一。本文参考“凤凰号”火星探测器的着陆过程,对火星软着陆障碍检测与规避技术进行研究,并进行相关的仿真演示平台的开发。
首先,基于CCD着陆相机采集的着陆区图像序列,分别对陨石坑和岩石障碍进行检测与识别。对陨石坑障碍,给出一种基于GVF-Snake动态模型的可靠闭合轮廓检测方法;对岩石障碍,给出一种基于多分辨率分析的快速岩石检测方法。对检测出的障碍,通过C-均值聚类方法计算出障碍目标大小及分布,并利用螺旋式搜索得到安全着陆点。
其次,根据检测出的安全着陆点,对障碍规避方法进行研究,给出了基于多项式求解两点边值问题的障碍规避方法和基于李雅普诺夫稳定理论的障碍规避方法。基于李雅普诺夫稳定理论的障碍规避方法考虑到地形威胁,将李雅普诺夫函数设计成状态函数与地形威胁势函数的折衷函数,进而求得探测器障碍规避控制律。
最后,在虚拟仿真引擎Delta3D开发环境下,对软着陆障碍检测与规避仿真演示平台进行开发,解决了视景仿真中多视口显示、虚拟相机数据采集和阴影生成等关键技术,实现了火星软着陆末段障碍检测与规避技术的可视化仿真与演示。
With the more deep exploration of Mars, the more complex terrain with higher scientific research value will go into detection range., which demands higher technique for soft landing task. The autonomous navigation technique with higher ability of obstacle detection and avoidance will become one of the key techniques in the future. In this paper, reference to the landing process of Phoenix Mars Lander, the research of the obstacle detection and hazard avoidance method is performed, and the related visual simulation platform is developed.
First of all, based on the image sequence obtained by CCD camera, the crater and rock are detected and identified respectively. A novel contour detection method based on GVF-Snake dynamic model is given for the detection of crater, and a rapid detection methods based on multi-resolution analysis is presented for the detection of rock. By the means of the C-means clustering method, the target size and distribution of obstacles are calculated, and then, a safe landing site is obtained by spiral search.
Secondly, according to the safe landing site, the research of hazard avoidance method is performed, a hazard avoidance method based on solving the special two-point boundary value problem and a algorithm based on Lyapunov stability method are given. The algorithm based on Lyapunov stability method take the threat of terrain dangerous into account, in this method, the Lyapunov function is designed as a compromise function of Energy function and terrain potential threat function,and then, the hazard avoidance guidance law is gained.
Finally, the simulation and demonstration platform for obstacle detection and hazard avoidance is developed in the development environment of visual simulation engine Delta3D, the key techniques in visual simulation such as multi-view, camera data acquisition and shadow generation is implemented, At last, the visual simulation of the obstacle detection and hazard avoidance in the terminal descent of soft landing is achieved.
首先,基于CCD着陆相机采集的着陆区图像序列,分别对陨石坑和岩石障碍进行检测与识别。对陨石坑障碍,给出一种基于GVF-Snake动态模型的可靠闭合轮廓检测方法;对岩石障碍,给出一种基于多分辨率分析的快速岩石检测方法。对检测出的障碍,通过C-均值聚类方法计算出障碍目标大小及分布,并利用螺旋式搜索得到安全着陆点。
其次,根据检测出的安全着陆点,对障碍规避方法进行研究,给出了基于多项式求解两点边值问题的障碍规避方法和基于李雅普诺夫稳定理论的障碍规避方法。基于李雅普诺夫稳定理论的障碍规避方法考虑到地形威胁,将李雅普诺夫函数设计成状态函数与地形威胁势函数的折衷函数,进而求得探测器障碍规避控制律。
最后,在虚拟仿真引擎Delta3D开发环境下,对软着陆障碍检测与规避仿真演示平台进行开发,解决了视景仿真中多视口显示、虚拟相机数据采集和阴影生成等关键技术,实现了火星软着陆末段障碍检测与规避技术的可视化仿真与演示。
With the more deep exploration of Mars, the more complex terrain with higher scientific research value will go into detection range., which demands higher technique for soft landing task. The autonomous navigation technique with higher ability of obstacle detection and avoidance will become one of the key techniques in the future. In this paper, reference to the landing process of Phoenix Mars Lander, the research of the obstacle detection and hazard avoidance method is performed, and the related visual simulation platform is developed.
First of all, based on the image sequence obtained by CCD camera, the crater and rock are detected and identified respectively. A novel contour detection method based on GVF-Snake dynamic model is given for the detection of crater, and a rapid detection methods based on multi-resolution analysis is presented for the detection of rock. By the means of the C-means clustering method, the target size and distribution of obstacles are calculated, and then, a safe landing site is obtained by spiral search.
Secondly, according to the safe landing site, the research of hazard avoidance method is performed, a hazard avoidance method based on solving the special two-point boundary value problem and a algorithm based on Lyapunov stability method are given. The algorithm based on Lyapunov stability method take the threat of terrain dangerous into account, in this method, the Lyapunov function is designed as a compromise function of Energy function and terrain potential threat function,and then, the hazard avoidance guidance law is gained.
Finally, the simulation and demonstration platform for obstacle detection and hazard avoidance is developed in the development environment of visual simulation engine Delta3D, the key techniques in visual simulation such as multi-view, camera data acquisition and shadow generation is implemented, At last, the visual simulation of the obstacle detection and hazard avoidance in the terminal descent of soft landing is achieved.
引文
[1] Golombek M P , Arvidson R E , Bell J FⅢ, et al. Assessment of Mars exploration rover landing site predictions. Nature, 2005,436(7074): 44-48
[2] P. Matthew, Cook, R. A., Moore, H. J., Parker. Selection of the Mars Pathfinder Landing Site. Journal of Geophysical Research. 1997, 9(2):3967~3988
[3] Nowicki S A, Christensen P R. Rock abundance on Mars from the thermal emission spectrometer. Journal of Geophysical Research, 2006, 112:1029-1132
[4] Seraji H. Fuzzy traversability index: a new concept for terrain-based navigation .Journal of Robotic Systems, 2000 , 17(2) :75-91
[5] Huertas A , Cheng Y, Madison R. Passive imaging based multi-cue hazard detection for spacecraft safe landing. IEEE, Aerospace Conference. 2006:14-22
[6] A. Grant, P. Matthew, J. Timothy Parker, A. Joy, W. Steven, M. Catherine. Selecting Landing Sites for the 2003 Mars Exploration Rovers. Planetary and Space Science. 2004, 17(32):11~21
[7] RichardP.Kornfeld, MarkD.Garcia, LynnE.Craig. Entry, Descent, and Landing Communications for the 2007 Phoenix Mars Lander. Journal of spacecraft and rockets, 2008,45(3):534-547
[8] H. Pien. Achieving Safe Antonomous Landing on Mars Using Vision-Based Approaches. 1612 Coorperative Intelligent Robotics in Space , 1991: 1~5
[9] T. Hashimoto , T. Kubota , T. Mizuno. Light weight sensors for the autonomous asteroid landing of MUSES-C mission. Acta Astronautica 52, 2003: 381~388
[10] C. Liebe, A. Randy K. Bartman, R. L. Bunker, J. Chapsky. Laser Radar for Spacecraft Guidance Applications. IEEE IEEEAC paper #1066, Updated December 11, 2002: 1005~1012
[11] A. Johnson, E. Skulsky, M. Bajracharya, E. Wong. Design of a Hazard Detection and Avoidance System for the Mars Smart Lander AIAA Atmospheric Flight Mechanics Conference, Monterey, CA, August 2002: 542~533
[12] A. Howard, H. Serajl. Multi-Sensor Terrain Classification for Safe Spacecraft Landing. IEEE Transactions on Aerospace and Electionic System, October 2004, 40(4): 291~316
[13] B. Leroy, G. Medioni, E. Johnson, L. Matthies. Crater detection for autonomous landing on asteroids. Image and Vision Computing , 2001: 787~792
[14] E. Johnson, H. Matthies. Precise Image-Based Motion Estimation for Autonomous Small Body Exploration. Jet Propulsion Laboratory report.1998: 1~43
[15] G. P. Guizzo, I. Vukman. Autonomous Smart Lander Simulator Based On Stereo Vision For The Descent Phase on Mars. IAC-03-IAC.10.3.06, 2003:1~3
[16] Larry Matthies, Andres Huertas, Yang Cheng and Andrew Johnson. Landing Hazard Detection with Stereo Vision and Shadow Analysis. AIAA 2007 Conference and Exhibit, California, 2007:1~10
[17] E. Bernard, P. Golombek. Crater and rock hazard modeling for mars landing. AIAA Space 2001 Conference and Exposition ,Albuquerque, NM Aug. 28-30, 2001: 1205~1211
[18] A. Johnson, A. Klumpp, J. Collier, A. Wolf. LIDAR-based Hazard Avoidance for Safe Landing on Mars. AAS/AIAA Space Flight Mechanics Meeting, Santa Barbara, 2001: 1021-1030
[19] E. Johnson, A. Miguel, San Martin. Motion Estimation from Laser Ranging for Autonomous Comet Landing. IEEE Robotics and Automation. 2000, 27(21):132~138
[20] J. Lafontanie. Laps: The Development of a Scanning Lidar System with GNC for Autonomous Hazard Avoidance and Precision Landing. Spaceborne Sensors. 2004, 13(8):81~93
[21]潘泉,于昕,程咏梅.信息融合理论的基本方法及进展.自动化学报. 2003, 29(4):599~609
[22] N. Serrano, M. Bajracharya, A. Howard, H. Seraji. A Novel Tiered Sensor Fusion Approach for Terrain Characterization and Safe Landing Assessment. IEEE Aerospace Conference Proceedings. 2005:1127~1139
[23] N. Serrano, E. Savakis, J. Luo. Improved Scene Classification Using Efficient Low-Level Features and Semantic Cues. Pattern Recognition. 2004, 27(18):1773~1784
[24] A. Ercoli Finizi, G. Gilardi, S. Acippi, P. Tedoldi. Automatic Optimu Moon-landing. 48thinternational Astronautical Congress. 1997: 1~7
[25] E. Wong, J. Masciarelli, G. Singh. Autonomous Guidance and Control Designfor Hazard Avoidance and Safe Landing on Mars. AIAA Atmospheric Flight Mechanics Conference, 2002: 1124~1130
[26] Yoshiro hamada, Tetsujiro ninomiya, yasuhiro Kstayama, Yasuo Shinomiya. Feasibility Study for Precise Lunar Landing using SELENE-B Lander Configuration. JAXA Reaearch and Development Report, 2005: 1~7
[27] G. L. Bauer, D. E. Cornick, and R. Stevenson. Capabilities and Application of the Program to Optimize Simulated Trajectories (POST). NASA CR-2770, 1997:235~251
[28] Jeffrey J. Biesiadeki, Abhinandan Jain, Mark L. James. Advanced Simulation Environment for Autonomous Spacecraft. Autonomous Robots. 1997,8(5):127-132
[29] J. Balaram, R. Austin, P. Banerjee, T. Bentley, D.Henriquez, B. Martin, E. McMahon, G. Sohl, DSENDS-A High-Fidelity Dynamics and Spacecraft Simulator for Entry, Descent and Surface Landing. IEEE 2002 Aerospace Conf., 2002:302~312
[30] S. A. Striepe, D. W. Way, A. M. Dwyer, J. Balaram. Mars Smart Lander Simulations for Entry, Descent, and landing. AIAA Atmospheric Flight Mechanics Conference and Exhibit, Monterey, California, 2002:1~13
[31] S. A. Striepe, D. W. Way, A. M. Dwyer, J. Balaram. Mars Science Laboratory Simulations for Entry, Descent and Landing. Journal of spacecraft and rockets, 2006:1~12
[32] J. Cuseo, C. Dallas and Martin Marietta. Planetary Terminal Descent Simulation with Autonomous Hazard Avoidance. AIAA 89-0515, 1989:1~10
[33]陈文娟,石民勇.蛇模型的综述.北京广播学院学报. 2003,10(2):17-20
[34]朱国平,吴小俊.基于GVF-Snake的运动目标跟踪.江南大学学报. 2008,7(4):408-413
[35]王海军,张有志.基于GVF模型的图像分割方法改进.计算机应用. 2006,26(5):1040-1043
[36] Mallat S G. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans on PAMI, 1989,11(7): 674-693
[37]王大轶,李铁寿,马兴瑞.月球最优软着陆两点边值问题的数值解法.航天控制, 2000年3月: 44~49
[38]王大轶.月球软着陆的制导控制研究.哈尔滨工业大学博士论文, 2000:2~16
[39]李斌,何济民.现代控制理论.重庆大学出版社. 2003:168-170
[40] M. Manning and M. Adler. Landing on Mars. AIAA Space 2005 Conference, September, 2005: 1102~1110
[41] A. Steltzner. Mars Science Laboratory Entry Descent and Landing System. Paper 1497, 2006 IEEE Aerospace Conference, Big Sky, Montana, March 2006: 345~350
[42]申闫春,.朱幼虹,曹莉,温转萍.基于OSG的三维仿真平台的设计与实现.计算机仿真. 2007, 24(6):1~2
[43]邓郑祥译. OpenGL编程指南.人民邮电出版社. 2005:473-475
[44] A. Bernatz, F. Thielecke. Navigation of a Low Flying VTOL Aircraft with the Help of a Downwards Pointing Camera. Control Engineering. 2004, 33(8):1~8
[45]吕品,张金芳.分布式仿真系统多通道视景生成.系统仿真学报. 2007,19(6):1291-1295
[46]宋志明,康凤举.视景仿真的关键技术.计算机应用. 2004,24(5):67~68
[47]薛守良,苏鸿根.实时阴影算法及实现.计算机应用. 2004,24(3):82-84
[48]李胜亮,管莉,张凌,潘伟,郝重阳.基于阴影映射的实时软阴影算法及实现.弹箭与制导学报. 2007,27(1):214-217
[49]沈潇.三维场景实时阴影算法研究与实现.重庆大学硕士论文, 2006: 18-39
[50]张勇,王莉.视景仿真系统中实时阴影绘制技术的研究.系统仿真学报. 2006, 18(1):180-186
[2] P. Matthew, Cook, R. A., Moore, H. J., Parker. Selection of the Mars Pathfinder Landing Site. Journal of Geophysical Research. 1997, 9(2):3967~3988
[3] Nowicki S A, Christensen P R. Rock abundance on Mars from the thermal emission spectrometer. Journal of Geophysical Research, 2006, 112:1029-1132
[4] Seraji H. Fuzzy traversability index: a new concept for terrain-based navigation .Journal of Robotic Systems, 2000 , 17(2) :75-91
[5] Huertas A , Cheng Y, Madison R. Passive imaging based multi-cue hazard detection for spacecraft safe landing. IEEE, Aerospace Conference. 2006:14-22
[6] A. Grant, P. Matthew, J. Timothy Parker, A. Joy, W. Steven, M. Catherine. Selecting Landing Sites for the 2003 Mars Exploration Rovers. Planetary and Space Science. 2004, 17(32):11~21
[7] RichardP.Kornfeld, MarkD.Garcia, LynnE.Craig. Entry, Descent, and Landing Communications for the 2007 Phoenix Mars Lander. Journal of spacecraft and rockets, 2008,45(3):534-547
[8] H. Pien. Achieving Safe Antonomous Landing on Mars Using Vision-Based Approaches. 1612 Coorperative Intelligent Robotics in Space , 1991: 1~5
[9] T. Hashimoto , T. Kubota , T. Mizuno. Light weight sensors for the autonomous asteroid landing of MUSES-C mission. Acta Astronautica 52, 2003: 381~388
[10] C. Liebe, A. Randy K. Bartman, R. L. Bunker, J. Chapsky. Laser Radar for Spacecraft Guidance Applications. IEEE IEEEAC paper #1066, Updated December 11, 2002: 1005~1012
[11] A. Johnson, E. Skulsky, M. Bajracharya, E. Wong. Design of a Hazard Detection and Avoidance System for the Mars Smart Lander AIAA Atmospheric Flight Mechanics Conference, Monterey, CA, August 2002: 542~533
[12] A. Howard, H. Serajl. Multi-Sensor Terrain Classification for Safe Spacecraft Landing. IEEE Transactions on Aerospace and Electionic System, October 2004, 40(4): 291~316
[13] B. Leroy, G. Medioni, E. Johnson, L. Matthies. Crater detection for autonomous landing on asteroids. Image and Vision Computing , 2001: 787~792
[14] E. Johnson, H. Matthies. Precise Image-Based Motion Estimation for Autonomous Small Body Exploration. Jet Propulsion Laboratory report.1998: 1~43
[15] G. P. Guizzo, I. Vukman. Autonomous Smart Lander Simulator Based On Stereo Vision For The Descent Phase on Mars. IAC-03-IAC.10.3.06, 2003:1~3
[16] Larry Matthies, Andres Huertas, Yang Cheng and Andrew Johnson. Landing Hazard Detection with Stereo Vision and Shadow Analysis. AIAA 2007 Conference and Exhibit, California, 2007:1~10
[17] E. Bernard, P. Golombek. Crater and rock hazard modeling for mars landing. AIAA Space 2001 Conference and Exposition ,Albuquerque, NM Aug. 28-30, 2001: 1205~1211
[18] A. Johnson, A. Klumpp, J. Collier, A. Wolf. LIDAR-based Hazard Avoidance for Safe Landing on Mars. AAS/AIAA Space Flight Mechanics Meeting, Santa Barbara, 2001: 1021-1030
[19] E. Johnson, A. Miguel, San Martin. Motion Estimation from Laser Ranging for Autonomous Comet Landing. IEEE Robotics and Automation. 2000, 27(21):132~138
[20] J. Lafontanie. Laps: The Development of a Scanning Lidar System with GNC for Autonomous Hazard Avoidance and Precision Landing. Spaceborne Sensors. 2004, 13(8):81~93
[21]潘泉,于昕,程咏梅.信息融合理论的基本方法及进展.自动化学报. 2003, 29(4):599~609
[22] N. Serrano, M. Bajracharya, A. Howard, H. Seraji. A Novel Tiered Sensor Fusion Approach for Terrain Characterization and Safe Landing Assessment. IEEE Aerospace Conference Proceedings. 2005:1127~1139
[23] N. Serrano, E. Savakis, J. Luo. Improved Scene Classification Using Efficient Low-Level Features and Semantic Cues. Pattern Recognition. 2004, 27(18):1773~1784
[24] A. Ercoli Finizi, G. Gilardi, S. Acippi, P. Tedoldi. Automatic Optimu Moon-landing. 48thinternational Astronautical Congress. 1997: 1~7
[25] E. Wong, J. Masciarelli, G. Singh. Autonomous Guidance and Control Designfor Hazard Avoidance and Safe Landing on Mars. AIAA Atmospheric Flight Mechanics Conference, 2002: 1124~1130
[26] Yoshiro hamada, Tetsujiro ninomiya, yasuhiro Kstayama, Yasuo Shinomiya. Feasibility Study for Precise Lunar Landing using SELENE-B Lander Configuration. JAXA Reaearch and Development Report, 2005: 1~7
[27] G. L. Bauer, D. E. Cornick, and R. Stevenson. Capabilities and Application of the Program to Optimize Simulated Trajectories (POST). NASA CR-2770, 1997:235~251
[28] Jeffrey J. Biesiadeki, Abhinandan Jain, Mark L. James. Advanced Simulation Environment for Autonomous Spacecraft. Autonomous Robots. 1997,8(5):127-132
[29] J. Balaram, R. Austin, P. Banerjee, T. Bentley, D.Henriquez, B. Martin, E. McMahon, G. Sohl, DSENDS-A High-Fidelity Dynamics and Spacecraft Simulator for Entry, Descent and Surface Landing. IEEE 2002 Aerospace Conf., 2002:302~312
[30] S. A. Striepe, D. W. Way, A. M. Dwyer, J. Balaram. Mars Smart Lander Simulations for Entry, Descent, and landing. AIAA Atmospheric Flight Mechanics Conference and Exhibit, Monterey, California, 2002:1~13
[31] S. A. Striepe, D. W. Way, A. M. Dwyer, J. Balaram. Mars Science Laboratory Simulations for Entry, Descent and Landing. Journal of spacecraft and rockets, 2006:1~12
[32] J. Cuseo, C. Dallas and Martin Marietta. Planetary Terminal Descent Simulation with Autonomous Hazard Avoidance. AIAA 89-0515, 1989:1~10
[33]陈文娟,石民勇.蛇模型的综述.北京广播学院学报. 2003,10(2):17-20
[34]朱国平,吴小俊.基于GVF-Snake的运动目标跟踪.江南大学学报. 2008,7(4):408-413
[35]王海军,张有志.基于GVF模型的图像分割方法改进.计算机应用. 2006,26(5):1040-1043
[36] Mallat S G. A theory for multiresolution signal decomposition: the wavelet representation. IEEE Trans on PAMI, 1989,11(7): 674-693
[37]王大轶,李铁寿,马兴瑞.月球最优软着陆两点边值问题的数值解法.航天控制, 2000年3月: 44~49
[38]王大轶.月球软着陆的制导控制研究.哈尔滨工业大学博士论文, 2000:2~16
[39]李斌,何济民.现代控制理论.重庆大学出版社. 2003:168-170
[40] M. Manning and M. Adler. Landing on Mars. AIAA Space 2005 Conference, September, 2005: 1102~1110
[41] A. Steltzner. Mars Science Laboratory Entry Descent and Landing System. Paper 1497, 2006 IEEE Aerospace Conference, Big Sky, Montana, March 2006: 345~350
[42]申闫春,.朱幼虹,曹莉,温转萍.基于OSG的三维仿真平台的设计与实现.计算机仿真. 2007, 24(6):1~2
[43]邓郑祥译. OpenGL编程指南.人民邮电出版社. 2005:473-475
[44] A. Bernatz, F. Thielecke. Navigation of a Low Flying VTOL Aircraft with the Help of a Downwards Pointing Camera. Control Engineering. 2004, 33(8):1~8
[45]吕品,张金芳.分布式仿真系统多通道视景生成.系统仿真学报. 2007,19(6):1291-1295
[46]宋志明,康凤举.视景仿真的关键技术.计算机应用. 2004,24(5):67~68
[47]薛守良,苏鸿根.实时阴影算法及实现.计算机应用. 2004,24(3):82-84
[48]李胜亮,管莉,张凌,潘伟,郝重阳.基于阴影映射的实时软阴影算法及实现.弹箭与制导学报. 2007,27(1):214-217
[49]沈潇.三维场景实时阴影算法研究与实现.重庆大学硕士论文, 2006: 18-39
[50]张勇,王莉.视景仿真系统中实时阴影绘制技术的研究.系统仿真学报. 2006, 18(1):180-186