Autonomous Precision Landing of Space Rockets - Lars Blackmore
10 days ago by jm
from 'Frontiers of Engineering: Reports on Leading-Edge Engineering' from the 2016 Symposium, published by the National Academies Press, regarding the algorithms used by SpaceX for their autonomous landings:spacex blue-origin convex-optimization space landing autonomous-vehicles flight algorithms
The computation must be done autonomously, in a fraction of a second. Failure to find a feasible solution in time will crash the spacecraft into the ground. Failure to find the optimal solution may use up the available propellant, with the same result. Finally, a hardware failure may require replanning the trajectory multiple times.
Suggested Citation:"Autonomous Precision Landing of Space Rockets - Lars Blackmore." National Academy of Engineering. 2017. Frontiers of Engineering: Reports on Leading-Edge Engineering from the 2016 Symposium. Washington, DC: The National Academies Press. doi: 10.17226/23659. ×
A general solution to such problems has existed in one dimension since the 1960s (Meditch 1964), but not in three dimensions. Over the past decade, research has shown how to use modern mathematical optimization techniques to solve this problem for a Mars landing, with guarantees that the best solution can be found in time (Açikmeşe and Ploen 2007; Blackmore et al. 2010).
Because Earth’s atmosphere is 100 times as dense as that of Mars, aerodynamic forces become the primary concern rather than a disturbance so small that it can be neglected in the trajectory planning phase. As a result, Earth landing is a very different problem, but SpaceX and Blue Origin have shown that this too can be solved. SpaceX uses CVXGEN (Mattingley and Boyd 2012) to generate customized flight code, which enables very high-speed onboard convex optimization.
10 days ago by jm
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