Suboptimal lunar landing GNC using nongimbaled optic-flow sensors

Sabiron, Guillaume; Raharijaona, Thibaut; Burlion, Laurent; Kervendal, Erwan; Bornschlegl, Eric; Ruffier, Franck

doi:10.1109/taes.2015.130573

Cited by 4 publications

(3 citation statements)

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“…Biomorphic course control is applied in robotics in special cases where processing capacity is limited and the robot is moving anyway. Examples include obstacle avoidance in small aerial robots (drones, e.g., Beyeler, Zufferey, and Floreano 2009) or in the design of a lunar landing device (Sabiron et al 2015).…”

Section: Beyond Insectsmentioning

confidence: 99%

In the Loop

2024

From Geometry to Behavior

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Section: Beyond Insectsmentioning

confidence: 99%

In the Loop

2024

From Geometry to Behavior

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“…In [18], three lunar landing control techniques were developed based on the various combinations of the terminal and programmed control methods. In [19], an optic-flow estimation-based nonlinear trajectory tracking method was applied to the lunar landing systems. To avoid the constraints on the thrust magnitude and look-angle in the terminal landing phase, a multi-constrained suboptimal guidance method based on the model predictive static programming technique was presented in [20].…”

Section: Introductionmentioning

confidence: 99%

Adaptive guidance and control of uncertain lunar landers in terminal landing phases

Sun

Jiang

2020

Mechanical Systems and Signal Processing

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A novel double-loop guidance and control strategy for under-actuated lunar landers in terminal landing phases is developed by using adaptive nonlinear control approach in this study. To derive the main thrust input and inner-loop desired attitude trajectory, the outer-loop position tracking guidance law is firstly developed based on the hyperbolic tangent functions to guarantee the constrained thrust and singularity avoidance of the desired attitudes. Then, to avoid the complicated analytic-derivative computing of the desired attitude trajectory, a stable second-order filter is employed to generate the command attitude trajectory for the inner-loop attitude motion. Finally, an adaptive attitude tracking controller is designed by combining the barrier Lyapunove function and the backstepping technique to get rid of the singularities of the 1 Euler angles-based attitude kinematic Jacobian matrix. In addition, tuning rules for designing parameters in guidance law and attitude controller are derived based on the Lyapunov analysis, and the pose tracking errors in the closed-loop system ultimately converge to the small neighborhoods of the origin. An example is simulated to verify the effectiveness of the proposed control design approach.

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“…The lander's objectives are to reach LG (10 m high) with both vertical and horizontal velocities of less than 1 m/s in absolute values and a pitch angle in the ±2 • range. Adapted from[16]. * indicates the optimality in terms of the mass, i.e., the fuel consumption).…”

mentioning

confidence: 99%

Optic flow-based nonlinear control and sub-optimal guidance for lunar landing

Sabiron¹,

Burlion²,

Raharijaona³

et al. 2014

2014 IEEE International Conference on Robotics and Biomimetics (ROBIO 2014)

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A sub-optimal guidance and nonlinear control scheme based on Optic Flow (OF) cues ensuring soft lunar landing using two minimalistic bio-inspired visual motion sensors is presented here. Unlike most previous approaches, which rely on state estimation techniques and multiple sensor fusion methods, the guidance and control strategy presented here is based on the sole knowledge of a minimum sensor suite (including OF sensors and an IMU). Two different tasks are addressed in this paper: the first one focuses on the computation of an optimal trajectory and the associated control sequences, and the second one focuses on the design and theoretical stability analysis of the closed loop using only OF and IMU measurements as feedback information. Simulations performed on a lunar landing scenario confirm the excellent performances and the robustness to initial uncertainties of the present guidance and control strategy.

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Suboptimal lunar landing GNC using nongimbaled optic-flow sensors

Abstract: Autonomous planetary landing is a critical phase in every exploratory space mission. Autopilots have to be safe, reliable, energy saving, and as light as possible. The 2-D guidance, navigation, and control strategy presented here makes use of biologically Manuscript

Cited by 4 publications

References 32 publications

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Adaptive guidance and control of uncertain lunar landers in terminal landing phases

Optic flow-based nonlinear control and sub-optimal guidance for lunar landing

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