#### Journal of Guidance, Control, and Dynamics

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ISSN / EISSN : 0731-5090 / 1533-3884
Total articles ≅ 7,846
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#### Latest articles in this journal

Yashwanth Kumar Nakka, Wolfgang Hönig, ChangRak Choi, Alexei Harvard, Amir Rahmani, Soon-Jo Chung
Published: 15 May 2022
Journal of Guidance, Control, and Dynamics pp 1-18; https://doi.org/10.2514/1.g006278

Abstract:
Inspection or mapping of a target spacecraft in a low Earth orbit using multiple observer spacecraft in stable passive relative orbits (PROs) is a key enabling technology for future space missions. Our guidance and control architecture uses an information gain approach to directly consider the tradeoff between gathered data and fuel/energy cost. The architecture has four components: information estimation, spacecraft’s absolute and relative state estimation, motion planning for relative orbit initialization and reconfiguration, and relative orbit control. The information estimation quantifies the information gain during inspection of a spacecraft, given past and potential future poses of all spacecraft. The estimated information gain is a crucial input to the motion planner, which computes PROs and reconfiguration strategies for each observer to maximize the information gain from distributed observations of the target spacecraft. The resulting motion trajectories jointly consider observational coverage of the target spacecraft and fuel/energy cost. For the PRO trajectories, a fuel-optimal attitude trajectory that minimizes rest-to-rest energy for each observer to inspect the target spacecraft is designed. The validation on a mission simulation to visually inspect the target spacecraft and on a three-degree-of-freedom robotic spacecraft dynamics simulator testbed demonstrates the effectiveness and versatility of our approach.
Puneet Jain, , Randal W. Beard
Published: 15 May 2022
Journal of Guidance, Control, and Dynamics pp 1-16; https://doi.org/10.2514/1.g006403

Abstract:
This paper presents theoretically justified controllers that use relative range and bearing measurements to steer a team of autonomous vehicles, operating without inertial position information, to circular trajectories around a constant-acceleration, constant-velocity, or stationary target. An extended Kalman filter is used to improve the noisy relative measurements and estimate the velocity of the moving target. These estimated values are used in the control laws to encircle constant-velocity moving targets. Lyapunov techniques are utilized to show that the vehicle will converge to the desired circular formations. Additionally, cooperating vehicles are shown to converge to a circular formation with equal temporal spacing using each vehicle’s estimate of the target’s velocity to define a common reference frame. Numerical simulations validate the efficacy of these control laws.
J. Humberto Ramos, Kevin M. Brink, Prashant Ganesh, John E. Hurtado
Published: 9 May 2022
Journal of Guidance, Control, and Dynamics pp 1-16; https://doi.org/10.2514/1.g006449

Abstract:
This work develops a factorized version of the partial-update Schmidt–Kalman filter: a partial-update filter that operates on the covariance matrix modified Cholesky factors $U$ (the upper triangular factor) and $D$ (a diagonal factor) rather than on the error covariance matrix $P$ . Effectively, this new formulation combines the well-known numerical stability properties of the UD factorized Kalman filter with the enhanced tolerance to high nonlinearities and uncertainties of the partial-update filter. Two versions of the UD partial-update filter are presented: one for sequential measurement processing, delivering the most computationally efficient update, and another for the more convenient but slightly more expensive batch measurement update. Additionally, an implementation of the partial update for the multiplicative extended Kalman filter and the associated quaternion attitude representation is provided. The efficacy of the UD partial-update filter is demonstrated via numerical simulations and hardware experiments; the results show that the combined UD partial-update filter provides a more robust filtering capability than when either component is used individually.
Travis W. Moleski, Jay P. Wilhelm
Published: 9 May 2022
Journal of Guidance, Control, and Dynamics pp 1-16; https://doi.org/10.2514/1.g006248

Abstract:
Navigation in Global Positioning System–denied environments is notoriously difficult for small unmanned aerial vehicles due to reduction of visible satellites and urban canyon multipath interference. Several existing methods can be used for navigating in a constrained environment, but they often require additional specific sensing hardware for a localization solution or only provide local frame navigation. Autonomous systems often include LiDAR and RGB cameras for mapping, sensing, or obstacle avoidance. Utilizing these sensors for navigation could provide the only or complimentary localization solutions to other Global Positioning System–denied localization methods in a global or local frame, especially in urban canyons where unique landmarks can be identified. Information from scanning LiDAR can be correlated with camera pixel coordinates and used to range unique visual landmarks that have known locations. The present work included surface function fitting to reduce ranging error to spherical landmarks since multiple lasers were able to range each landmark. Simulation and experimental validation of the unique camera–LiDAR modified trilateration process was undertaken using colored light orbs as landmarks with a 16-laser scanning LiDAR and known positions. Position error was computed and verified that the position estimate process was successful at varying landmark configurations and viewing angles in simulation. Experimental results verified the process while also providing higher accuracy than a previous method of using a single point on landmark surfaces, for the tested setup.
, Ramon Calvo, Adrian Trujillo, ,
Published: 2 May 2022
Journal of Guidance, Control, and Dynamics pp 1-15; https://doi.org/10.2514/1.g006828

Abstract:
An optimization algorithm for planning the motion of a humanoid robot during extravehicular activities is presented in this paper. The algorithm can schedule and plan the movements of the two robotic arms to move the humanoid robot by using the handrails present outside the International Space Station. The optimization algorithm considers the eventual constraints imposed by the topology of the handrails and calculates the sequence of grasping and nongrasping phases needed to push and pull the robot along the handrails. A low-level controller is also developed and used to track the planned arms and end-effectors trajectories. Numerical simulations assess the applicability of the proposed strategy in three different typical operations that potentially can be performed in an extravehicular activity scenario.
Marco A. G. Moreira, Juliano A. B. Gripp, Takashi Yoneyama, Cleverson M. P. Marinho
Published: 2 May 2022
Journal of Guidance, Control, and Dynamics pp 1-11; https://doi.org/10.2514/1.g006443

Yu Wang, Aijun Li, Haochang Tian,
Published: 2 May 2022
Journal of Guidance, Control, and Dynamics pp 1-8; https://doi.org/10.2514/1.g006682

S. P. Arjun Ram, Maruthi R. Akella
Published: 2 May 2022
Journal of Guidance, Control, and Dynamics pp 1-8; https://doi.org/10.2514/1.g006184

Raziye Tekin
Published: 2 May 2022
Journal of Guidance, Control, and Dynamics pp 1-7; https://doi.org/10.2514/1.g006736

Rafy Kfir, Gyorgy Hexner, Joseph Z. Ben-Asher
Published: 2 May 2022
Journal of Guidance, Control, and Dynamics pp 1-8; https://doi.org/10.2514/1.g006218