# Integrated Guidance and Control for Lunar Landing using a Stabilized Seeker

arXiv: https://arxiv.org/abs/2112.08540 · HTML: https://mlsanity.com/paper/2112.08540/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 21 references that are in the map.
- First posted on arXiv 16 Dec 2021.

## Builds on (most cited first, 8 of 8)

- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks](https://mlsanity.com/paper/1703.03400/) (2017)
- [Trust Region Policy Optimization](https://mlsanity.com/paper/1502.05477/) (2015)
- [Learning to reinforcement learn](https://mlsanity.com/paper/1611.05763/) (2016)
- [Meta Learning Shared Hierarchies](https://mlsanity.com/paper/1710.09767/) (2017)
- [Gated Feedback Recurrent Neural Networks](https://mlsanity.com/paper/1502.02367/) (2015)
- [Deep Reinforcement Learning for Six Degree-of-Freedom Planetary Powered Descent and Landing](https://mlsanity.com/paper/1810.08719/) (2018)
- [Reinforcement Meta-Learning for Interception of Maneuvering Exoatmospheric Targets with Parasitic Attitude Loop](https://mlsanity.com/paper/2004.09978/) (2020)

## Built on by (most cited first, 1 of 1)

- [Deep Reinforcement Learning for Weapons to Targets Assignment in a Hypersonic strike](https://mlsanity.com/paper/2310.18509/) (2023)

## Abstract (arXiv)

We develop an integrated guidance and control system that in conjunction with a stabilized seeker and landing site detection software can achieve precise and safe planetary landing. The seeker tracks the designated landing site by adjusting seeker elevation and azimuth angles to center the designated landing site in the sensor field of view. The seeker angles, closing speed, and range to the designated landing site are used to formulate a velocity field that is used by the guidance and control system to achieve a safe landing at the designated landing site. The guidance and control system maps this velocity field, attitude, and rotational velocity directly to a commanded thrust vector for the lander's four engines. The guidance and control system is implemented as a policy optimized using reinforcement meta learning. We demonstrate that the guidance and control system is compatible with multiple diverts during the powered descent phase, and is robust to seeker lag, actuator lag and degradation, and center of mass variation induced by fuel consumption. We outline several concepts of operations, including an approach using a preplaced landing beacon.