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San Martin, A. Miguel

Publications and source records attributed to San Martin, A. Miguel.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Design and Development of High-Performance Imaging Lidars for Extreme Radiation Environments of Europa

To enable safe landing on unknown terrain, such as Europa, JPL has been developing two next-generation dual-mode lidars that can provide long range altimetry as well as dense 3D mapping in real-time during landing. In this paper, we discuss the overall concept, development strategy and report on the detailed progress of the lidar development. Besides, the use for Europa, the flexible design and reconfigurability of lidars allow for a wide range of operation on other planetary bodies.

Machan, Roman↗
NASA NTRS2022

Vision-based Velocimetry over Unknown Terrain with a Low-Noise IMU

This paper presents a novel approach to terrain-relative navigation with a visual camera and Inertial Measurement Unit (IMU). The proposed algorithm uses an Extended Kalman Filter (EKF) to combine an IMU propagated state estimate with batch correction estimates computed over a sliding window of measurements. The batch correction algorithm follows the Maximum Likelihood Estimation (MLE) approach used in other Bundle Adjustment systems. Unlike other systems, the proposed system parameterizes the state over the entire window in terms of the state at a single epoch. By ignoring IMU error over the window duration, we obtain a state epoch MLE that jointly estimates the epoch state and terrain parameters with drastically reduced computationally cost. This paper presents the general architecture which can be adapted for various state parameterizations and measurement inputs. For space applications with high-accuracy IMUs, the reduction in computational cost comes with only a modest increase in estimation errors. The increase in error is quantified via a linear covariance analysis presented in this paper. Furthermore, we present simulation results which show the applicability of this algorithm to planetary landing problems.

San Martin, A. Miguel↗
NASA NTRS2021

The Mars 2020 Perseverance Navigation Filter

The Mars 2020 (M2020) Entry Descent and Landing (EDL) system delivered a rover named “Perseverance” at Jezero crater (Mars) on February 18th, 2021. M2020 EDL used a Guidance Navigation and Control (GN&C) system to achieve its landing target objectives. The navigation filter (NavFilter) integrated Descent Inertial Measurement Unit (DIMU) measurements to estimate position and attitude. The NavFilter also used the Terminal Descent Sensor (TDS) to es-timate surface-relative position and velocity corrections. The NavFilter provided all of the dynamic state information to the entry controller, entry guidance, Lander Vision System (LVS) and powered descent guidance and control algo-rithms. The NavFilter for Perseverance is based on Curiosity’s NavFilter with a couple of modifications.

Casoliva, Jordi↗
NASA NTRS2021

Analysis of Mars 2020 Perseverance Entry, Descent, and Landing Attitude Initialization Performance

The Mars 2020 Perseverance rover successfully landed at Jezero Crater on February 18, 2021. To perform this feat, the entry, descent, and landing navigation filter must be initialized with an estimate of the spacecraft state, which includes attitude from the cruise attitude control subsystem. Accuracy of this initial attitude estimate has an impact on important metrics such as touchdown velocity. This paper presents a post-landing reconstruction of the attitude initialization error budget, showing that the requirement of 0.15 deg ($3\sigma$, per axis) was met. Each error source is described and analyzed, including flight telemetry where possible. Analysis of the error budget shows that it is driven by systematic sun sensor errors, star-scanner-to-sun-sensor alignment stability, and inertial-measurement-unit-to-sun-sensor alignment stability. Finally, a contingency plan to initialize the navigation filter in the event of a star scanner failure is presented. While this plan was not needed in flight, results indicate that the attitude initialization requirement could have still been met in this off-nominal scenario.

Lo, Kevin D.↗
NASA NTRS2018

A Hazard Detection Sensor for Landing on Europa

Based on the limited imagery available, the surface topography of Jupiter’s icy moon Europa is expected to be hazardous for robotic landers. The Europa Lander Concept Pre-Project Team has therefore concluded that onboard hazard detection (and avoidance) using an imaging light detection and ranging (lidar) system is an enabling technology. In this paper we describe the challenges, requirements, technical solution space, and our maturation strategy to advance lidar technology for a Europa Lander mission concept to TRL 6 by 2021. JPL is confident that the resulting technology will be of value to a wide range of lunar and planetary landing missions.

Katake, Anup↗
NASA NTRS2017

A Minimal State Augmentation Algorithm for Vision-Based Navigation without Using Mapped Landmarks

This paper describes MAVeN (Minimal State Augmentation Algorithm for Vision-Based Navigation), which is a new algorithm for vision-based navigation that has only 21 states, yet is able to track features in successive camera images and use them to propagate estimates of the spacecraft position and velocity. The filter dimension drops to 12 if attitude information is already available. The low filter dimension makes MAVeN a very reliable and practical algorithm for real-time flight implementation. The main idea is to project observed features onto a rough shape model of the ground surface, which are then used by the filter as pseudo-landmarks. The shape model is assumed to be known beforehand, as would be obtained from prior surveillance of the landing site from orbit. MAVeN does not require pre-mapped landmarks, so it is able to navigate terrain that has not been previously observed up close. This property is especially important for close proximity operations in small body missions where ground surface features are being seen for the first time at close range. MAVeN is also able to hover motionless above the ground without position error growth, which is unusual for this class of vision-based navigation algorithms.

San Martin, A. Miguel↗
NASA NTRS2017

Landing on Europa: Challenges, Technologies, and a Strategy

Jupiter’s moon Europa is of intense scientific interest because of the vast quantities of salty liquid water which likely lay beneath its thin icy crust and the tantalizing prospect of finding life elsewhere in the solar system. The planned Europa Mission, which would perform remote science through multiple flybys of Europa, is under development and promises to yield unprecedented insight into this intriguing body. However, there remains a strong desire in the scientific community to perform in situ Europa science through a landed mission. Europa presents unique challenges to a landing mission because of its hostile radiation environment and the lack of information about its terrain. As a complement to the flyby mission, a bold concept to land on Europa and perform in situ science is being studied. Such a mission requires significant technology development to overcome the inherent landing challenges. This paper provides a brief overview of the Europa Lander mission concept and its notional objectives. It then describes the significant challenges associated with landing on Europa, the technologies required to overcome those challenges, and a strategy for Deorbit, Descent, and Landing.

Frick, Andreas↗
NASA NTRS2013

The Development of the MSL Guidance, Navigation, and Control System for Entry, Descent, and Landing

On August 5, 2012, the Mars Science Laboratory (MSL) mission successfully delivered the Curiosity rover to its intended target. It was the most complex and ambitious landing in the history of the red planet. A key component of the landing system, the requirements for which were driven by the mission ambitious science goals, was the Guidance, Navigation, and Control (GN&C) system. This paper will describe the technical challenges of the MSL GN&C system, the resulting architecture and design needed to meet those challenges, and the development process used for its implementation and testing.

GN&C↗