Relevant bibliographies by topics / Spacecraft path planning

Academic literature on the topic 'Spacecraft path planning'

Author: Grafiati
Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Spacecraft path planning"

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Zhang, Zhen, Qun Fang, Jinfeng Song, Xiuwei Zhang, and Zhanxia Zhu. "Research on dynamic path planning algorithm of spacecraft cluster based on cooperative particle swarm algorithm." Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 39, no. 6 (December 2021): 1222–32. http://dx.doi.org/10.1051/jnwpu/20213961222.

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In order to solve the problem of path planning for the spacecraft cluster to reach the dynamic target point under the premise of considering obstacle avoidance. In view of the fixed search radius, it will be difficult for the spacecraft to find a better value when it is close to the target point. This paper converts the orbital dynamics of each member spacecraft into an optimization problem considering constraints, and proposes an improved CPSO algorithm based on coordination. The path planning method of the traditional particle swarm optimization (CPSO): The dynamic radius search method that changes the search radius by changing the distance between them, and improves the CPSO algorithm based on this. The improved CPSO algorithm autonomously finds the optimal path of each member spacecraft at the current moment through the dynamic search radius, thereby obtaining the optimal solution for the dynamic path planning of the spacecraft cluster in three-dimensional space. The simulation results show that the use of the improved CPSO algorithm can not only obtain the optimal solution to the spacecraft cluster dynamic path planning problem, but also greatly reduce the fuel consumption in its path planning and improve the path stability of each member spacecraft.
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Sultan, Cornel, Sanjeev Seereram, and Raman K. Mehra. "Deep Space Formation Flying Spacecraft Path Planning." International Journal of Robotics Research 26, no. 4 (April 2007): 405–30. http://dx.doi.org/10.1177/0278364907076709.

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Duan, Chao, Qinglei Hu, Youmin Zhang, and Huaining Wu. "Constrained single-axis path planning of underactuated spacecraft." Aerospace Science and Technology 107 (December 2020): 106345. http://dx.doi.org/10.1016/j.ast.2020.106345.

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Wu, Xiao Wen, Lin Zhao, Yong Hao, Bo Zhang, and Shuai Chen. "Sinusoidal Path Planning for Attitude Maneuver of Flexible Spacecraft." Applied Mechanics and Materials 532 (February 2014): 187–90. http://dx.doi.org/10.4028/www.scientific.net/amm.532.187.

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Considering the complex of space environment, the influence of flexible attachments, the restraint of measurement and control precision, it makes difficult to control the attitude precisely. In order to improve the attitude maneuver's rapidity and its stability, this paper studied the attitude maneuver's path programming method of satellite with the flexible attachments. Through the establishment of the dynamic model of flexible satellites, and using multi-objective optimization algorithm to select the optimal parameter, an asymmetric sinusoidal maneuver path was planned. Simulation results show that the planned path could suppress flexible appendages vibration which brought by attitude changes, then the effectiveness of the planning algorithm is demonstrated.
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Hua, Bing, Guang Yang, Yunhua Wu, and Zhiming Chen. "Path Planning of Spacecraft Cluster Orbit Reconstruction Based on ALPIO." Remote Sensing 14, no. 19 (September 23, 2022): 4768. http://dx.doi.org/10.3390/rs14194768.

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An adaptive learning pigeon-inspired optimization based on mutation disturbance (ALPIO) is proposed for solving the problems of fuel consumption and threat avoidance in spacecraft cluster orbit reconstruction. First, considering the constraints of maintaining a safe distance between adjacent spacecraft within the spacecraft cluster and of avoiding space debris, the optimal performance index for orbital reconfiguration is proposed based on the fuel consumption required for path planning. Second, ALPIO is proposed to solve the path planning. Compared with traditional pigeon-inspired optimization, ALPIO uses the initialization of chaotic and elite backward learning to increase the population diversity, using a nonlinear weighting factor and adjustment factor to control the speed and accuracy of prepopulation convergence. The Cauchy mutation was implemented in the map and compass operator to prevent the population from falling into local optima, and the Gaussian mutation and variation factor were utilized in the landmark operator to prevent the population from stagnating in the late evolution. Through simulation experiments using nine test functions, ALPIO is shown to significantly improve accuracy when obtaining the optimum compared with PSO, PIO, and CGAPIO, and orbital reconfiguration consumes less total fuel. The trajectory of path planning for ALPIO is smoother than those of other optimization methods, and its obstacle avoidance path is the most stable.
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Guzzetti, Davide, and Hexi Baoyin. "Human Path-Planning for Autonomous Spacecraft Guidance at Binary Asteroids." IEEE Transactions on Aerospace and Electronic Systems 55, no. 6 (December 2019): 3126–38. http://dx.doi.org/10.1109/taes.2019.2899795.

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OKUBO, Hiroshi, Nobuo NAGANO, and Nobuo KOMATSU. "Path Planning of Space Manipulators to Reduce Spacecraft Attitude Disturbances." Transactions of the Japan Society of Mechanical Engineers Series C 65, no. 637 (1999): 3678–85. http://dx.doi.org/10.1299/kikaic.65.3678.

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Zhang, Jiawei, Kemao Ma, and Guizhi Meng. "Controllability analysis and attitude path planning of underactuated spacecraft systems." Aerospace Science and Technology 33, no. 1 (February 2014): 76–81. http://dx.doi.org/10.1016/j.ast.2014.01.003.

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Xu, Rui, Hui Wang, Wenming Xu, Pingyuan Cui, and Shengying Zhu. "Rotational-path decomposition based recursive planning for spacecraft attitude reorientation." Acta Astronautica 143 (February 2018): 212–20. http://dx.doi.org/10.1016/j.actaastro.2017.11.035.

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Wu, Changqing, and Xiaodong Han. "Energy-optimal spacecraft attitude maneuver path-planning under complex constraints." Acta Astronautica 157 (April 2019): 415–24. http://dx.doi.org/10.1016/j.actaastro.2018.12.028.

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Dissertations / Theses on the topic "Spacecraft path planning"

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Aoudé, Georges Salim. "Two-stage path planning approach for designing multiple spacecraft reconfiguration maneuvers and application to SPHERES onboard ISS." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42050.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2007.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 143-149).
The thesis presents a two-stage approach for designing optimal reconfiguration maneuvers for multiple spacecraft. These maneuvers involve well-coordinated and highly-coupled motions of the entire fleet of spacecraft while satisfying an arbitrary number of constraints. This problem is particularly difficult because of the nonlinearity of the attitude dynamics, the non-convexity of some of the constraints, and the coupling between the positions and attitudes of all spacecraft. As a result, the trajectory design must be solved as a single 6N DOF problem instead of N separate 6 DOF problems. The first stage of the solution approach quickly provides a feasible initial solution by solving a simplified version without differential constraints using a bi-directional Rapidly-exploring Random Tree (RRT) planner. A transition algorithm then augments this guess with feasible dynamics that are propagated from the beginning to the end of the trajectory. The resulting output is a feasible initial guess to the complete optimal control problem that is discretized in the second stage using a Gauss pseudospectral method (GPM) and solved using an off-the-shelf nonlinear solver. This thesis also places emphasis on the importance of the initialization step in pseudospectral methods in order to decrease their computation times. It demonstrates the improvement that an initial guess based on an RRT planner brings to an optimal control problem solved using pseudospectral methods. Finally, this thesis presents the successful results of several reconfiguration maneuver experiments performed using the Synchronized Position Hold Engage and Reorient Experimental Satellites (SPHERES) hardware testbed onboard the International Space Station (ISS). The maneuvers were designed using two different two-stage algorithms presented in this work. It also discusses the lessons learned from these tests, and the recommendations to improve future ISS reconfiguration experiments.
by Georges Salim Aoudé.
S.M.
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Book chapters on the topic "Spacecraft path planning"

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Meng, Shaohua, Lijian Zhang, Ruiqin Hu, Peng Zheng, and Feng Gao. "Path Planning for Large-Scale Spacecraft Components Assembly in Confined Space Using Industrial Robot." In Advances in Intelligent Systems and Computing, 660–68. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00214-5_83.

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Okoloko, Innocent. "Multi-Spacecraft Attitude Path Planning Using Consensus with LMI-Based Exclusion Constraints." In Advanced Path Planning for Mobile Entities. InTech, 2018. http://dx.doi.org/10.5772/intechopen.71580.

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Conference papers on the topic "Spacecraft path planning"

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Pennecot, Y., E. Atkins, and R. Sanner. "Intelligent spacecraft formation management and path planning." In 40th AIAA Aerospace Sciences Meeting & Exhibit. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2002. http://dx.doi.org/10.2514/6.2002-1072.

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Paluszek, Michael, and Stephanie Thomas. "Generalized 3D Spacecraft Proximity Path Planning Using A*." In Infotech@Aerospace. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2005. http://dx.doi.org/10.2514/6.2005-7043.

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Sipowa, Hermann K., and Jay W. McMahon. "Fuel-Efficient Distributed Path Planning for Spacecraft Formation Flying." In 2022 IEEE Aerospace Conference (AERO). IEEE, 2022. http://dx.doi.org/10.1109/aero53065.2022.9843443.

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Munoz, Josue, George Boyarko, and Norman Fitz-Coy. "Rapid Path-Planning Options for Autonomous Proximity Operations of Spacecraft." In AIAA/AAS Astrodynamics Specialist Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-7667.

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Ai, Qingmu, Hongwei Fan, Qian Wang, and Shunli Li. "Spacecraft dynamics modeling and attitude control based on Path Planning." In 2021 IEEE 4th International Conference on Information Systems and Computer Aided Education (ICISCAE). IEEE, 2021. http://dx.doi.org/10.1109/iciscae52414.2021.9590768.

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Okoloko, I. "Path planning for multiple spacecraft using consensus with LMI avoidance constraints." In 2012 IEEE Aerospace Conference. IEEE, 2012. http://dx.doi.org/10.1109/aero.2012.6187118.

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L'Afflitto, Andrea, and Cornel Sultan. "Applications of Calculus of Variations to Aircraft and Spacecraft Path Planning." In AIAA Guidance, Navigation, and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2009. http://dx.doi.org/10.2514/6.2009-6073.

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L`Afflitto, Andrea, and Cornel Sultan. "On Calculus of Variations in Aircraft and Spacecraft Formation Flying Path Planning." In AIAA Guidance, Navigation, and Control Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-8018.

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Radmanesh, Mohammadreza, and Manish Kumar. "UAV Path Planning in the Framework of MILP-Tropical Optimization." In ASME 2017 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/dscc2017-5231.

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This paper proposes a fast method for obtaining mathematically optimal trajectories for UAVs while avoiding collisions. A comparison of the proposed method with previously used Mixed Integer Linear Programming (MILP) to find the optimal collision-free path UAVs, aircraft, and spacecraft show the effectiveness and performance of this method. Here, the UAV path planning problem is formulated in the new framework named MILP-Tropical optimization that exploits tropical mathematics for obtaining solution and then casted in a novel branch-and-bound method. Various constraints including UAV dynamics are incorporated in the proposed Tropical framework and a solution methodology is presented. An extensive numerical study shows that the proposed method provides faster solution. The proposed technique can be extended to distributed control for multiple vehicles and multiple way-points.
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Yu, Zhen, Yu Guo, Chenxing Zhong, Lu Wang, and Wei Yao. "Vibration suppression of flexible spacecraft using smart materials and path planning during attitude maneuver." In 2014 33rd Chinese Control Conference (CCC). IEEE, 2014. http://dx.doi.org/10.1109/chicc.2014.6895568.

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