Searching safe landing site with parameters optimization based on genetic algorithm

Liu, Xianggen; Zhong, Huasong; Chang, Sheng; Meng, Yi

doi:10.1109/iccwamtip.2014.7073370

Cited by 2 publications

(1 citation statement)

References 7 publications

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“…For optimal landing site selection, the selection index of the safe landing site was given by Johnson and Simo˜es, but positioning the safe landing site was not reported. 10,14,15 Liu et al 16 adopted genetic algorithm (GA) to identify a safe landing site from the gray images, which is heavily subject to the false detection and missing detection rate; at the same time, several minutes are needed to accomplish image processing and optimization computation. Du et al 17 adopted particle swarm optimization (PSO) to select a safe landing point in the 3D elevation map, which is difficult to apply to engineering practice due to its considerable complexity and large computation burden.…”

Section: Introductionmentioning

confidence: 99%

Innovative hazard detection and avoidance guidance for safe lunar landing

Jiang

Tao

2016

Proceedings of the Institution of Mechanical Engineers, Part G:

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Safe planetary landing is considered a key technology for future robotic and manned planetary landing missions. The relay hazard detection and proportion–integration–differentiation avoidance guidance algorithms were used in Chang’e-3 mission, which not only increased the complexity of the guidance system, but also resulted in non-fuel-optimal avoidance guidance from the viewpoint of fuel consumption. To further develop and improve the hazard detection and avoidance scheme of Chang’e-3, novel autonomous hazard avoidance methodologies should be investigated. This paper addresses an innovative hazard detection and avoidance scheme for safe lunar landing from the following three aspects: imaging flash lidar based hazard detection, safe landing site selection strategy, and minimum-fuel hazard avoidance guidance. First, the three-dimensional imaging flash lidar, a developing three-dimensional imaging sensor, is utilized to rapidly and precisely detect three-dimensional terrain of the landing area. Second, the hazard detection and optimum landing site selection strategy inherited from Chang’e-3 are improved and enhanced to estimate the potential obstacles, and select an optimum landing site which is the guidance target of following hazard avoidance. Next, the fuel-optimal hazard avoidance guidance problem is transcribed into as a minimum-fuel consumption optimization problem using the Gauss pseudospectral method, which is easily solved by the open-source software GPOPS. Finally, the validity of the autonomous hazard detection and avoidance guidance scheme proposed in this paper is confirmed by computer simulation.

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