Testing for the MMX Rover Autonomous Navigation Experiment on Phobos

The MMX rover will explore the surface of Phobos, Mars´ bigger moon. It will use its stereo cameras for perceiving the environment, enabling the use of vision based autonomous navigation algorithms. The German Aerospace Center (DLR) is currently developing the corresponding autonomous navigation experiment that will allow the rover to efficiently explore the surface of Phobos, despite limited communication with Earth and long turn-around times for operations. This paper discusses our testing strategy regarding the autonomous navigation solution. We present our general testing strategy for the software considering a development approach with agile aspects. We detail, how we ensure successful integration with the rover system despite having limited access to the flight hardware. We furthermore discuss, what environmental conditions on Phobos pose a potential risk for the navigation algorithms and how we test for these accordingly. Our testing is mostly data set-based and we describe our approaches for recording navigation data that is representative both for the rover system and also for the Phobos environment. Finally, we make the corresponding data set publicly available and provide an overview on its content

Mobility on the Surface of Phobos for the MMX Rover - Simulation-aided Movement planning

The MMX Rover, recently named IDEFIX, will be the first wheeled robotic system to be operated in a milli-g environment. The mobility in this environment, particularly in combination with the interrupted communication schedule and the activation of on-board autonomous functions such as attitude control requires efficient planning. The Mobility Group within the MMX Rovers Team is tasked with proposing optimal solutions to move the rover safely and efficiently to its destination so that it may achieve its scientific goals. These movements combine various commands to the locomotion system and to the navigation systems developed by both institutions. In the mission's early phase, these actions will rely heavily on manual driving commands to the locomotion system until the rover behavior and environment assumptions are confirmed. Planning safe and efficient rover movements is a multi-step process. This paper focuses on the challenges and limitations in sequencing movements for a Rover on Phobos in the context of the MMX Mission. The context in which this process takes place is described in terms of available data and operational constraints

Data fusion framework for planetary and orbital robotics applications

In space robotics, a wide range of sensor data fusion methods are required to accomplish challenging objectives for exploration, science and commercial purposes. This includes navigation for planetary and guidance for orbital robotics, scientific prospecting, and on-orbit servicing. In Fuse provides a comprehensive data fusion framework or toolset to fuse and interpret sensor data from multiple sensors. This project represents an optimal approach to develop software for robotics: a standardized and comprehensive development environment for industrial applications, with particular focus on space applications where components can be connected, tested offline, evaluated and deployed in any preferred robotic framework, including those devised for space or terrestrial applications. This paper discusses the results of verification and validation of data fusion methods for robots deployed in orbital and planetary scenarios using data sets collected in simulation and outdoor analogue campaigns

Preliminary Results for the Multi-Robot, Multi-Partner, Multi-Mission, Planetary Exploration Analogue Campaign on Mount Etna

This paper was initially intended to report on the outcome of the twice postponed demonstration mission of the ARCHES project. Due to the global COVID pandemic, it has been postponed from 2020, then 2021, to 2022. Nevertheless, the development of our concepts and integration has progressed rapidly, and some of the preliminary results are worthwhile to share with the community to drive the dialog on robotics planetary exploration strategies. This paper includes an overview of the planned 4-week campaign, as well as the vision and relevance of the missiontowards the planned official space missions. Furthermore, the cooperative aspect of the robotic teams, the scientific motivation, the sub task achievements are summarised

Finally! Insights into the ARCHES Lunar Planetary Exploration Analogue Campaign on Etna in summer 2022

This paper summarises the first outcomes of the space demonstration mission of the ARCHES project which could have been performed this year from 13 june until 10 july on Italy’s Mt. Etna in Sicily. After the second postponement related to COVID from the initially for 2020 planed campaign, we are now very happy to report, that the whole campaign with more than 65 participants for four weeks has been successfully conduced. In this short overview paper, we will refer to all other publication here on IAC22. This paper includes an overview of the performed 4-week campaign and the achieved mission goals and first results but also share our findings on the organisational and planning aspects

Towards an FDIR Software Fault Tree Library for Onboard Computers

The increasing complexity of space missions, their software architectures, and hardware that has to meet the demands for those missions, imposes numerous new challenges for many engineering disciplines such as reliability engineering. Affected by the ever growing demand for more onboard computation power are the onboard computers. They in return require Fault Detection, Isolation, and Recovery (FDIR) architectures to support their fault tolerant operation in the harsh environment of space. Especially high performance commercial processing units face the challenge of dealing with negative radiation effects, which may significantly degrade their operation. To design performant and fault tolerant onboard computers, it is of high interest to assess the effectiveness of the FDIR architecture in the early phase of system design. This can be achieved using Fault Tree Analysis (FTA). However, to create complete fault trees manually is an error prone and labor intensive task. In this paper, the methodology for assessing the FDIR design of onboard computers in space systems, presented in [1], is refined by introducing a library of FDIR routines. The routines are modeled using fault trees and are composed into a software system fault tree using a basic fault model and a design configuration chosen by the reliability engineer. To assess the configurations, we give a heuristic based on a factor-criteria-metric model. We demonstrate the feasability of our approach on the basis of a case study on the rover of the Martian Moons eXploration (MMX) mission. Several FDIR configurations are studied and fault trees are generated for them. For the chosen case study, we obtain a reduction of up to 80% in terms of modeling effort

Datasets of Long Range Navigation Experiments in a Moon Analogue Environment on Mount Etna

Long range navigation capabilities are crucial to increase the level of autonomy for robotic planetary exploration missions. As the opportunities to collect data on the surfaces of other planets are both very limited and expensive, space analogue sites on Earth play an important role to develop and test robotic systems. We provide and present two datasets captured with our Lightweight Rover Unit (LRU) at a planetary surface analogue test site on Mt. Etna, Sicily, Italy. In distinction to many other robot navigation datasets, we were able to capture datasets in an environment that is in terms of its visual and terramechanical properties close to the character of surfaces of rocky planets, hence making our data valuable for the development of visual-inertial navigation systems for planetary and unstructured GPS-denied outdoor environments. We make both of our datasets publicly available and free to download for other researchers to use them to test, improve and evaluate their navigation methods. We provide raw data in the form of ROS bagfiles containing gray-scale images, dense depth images, sensor readings from an Inertial Measurement Unit (IMU) and wheel odometry estimates. In addition, the data contains ground truth for the rover trajectory obtained via differential GPS (DGPS) to allow an evaluation of robot localization methods. The datasets were recorded during experiments, in which our rover traversed paths of approximately 1 km in length each. This makes them useful for testing pose estimation methods over long ranges

Roving on Phobos: Challenges of the MMX Rover for Space Robotics

This paper presents a small rover for exploration mission dedicated to the moons of Mars, Phobos and Deimos. This project is a collaboration between JAXA for the mother spacecraft, and a cooperative contribution of CNES and DLR to provide a rover payload. This rover will be different in many aspects compared to the existing ones. It will have to drive in a very low gravity with only little power given by the solar arrays. It will also need autonomy in order to achieve a consequent distance during a short mission of 100 days. Apart of the technology demonstration driven mission aspects, the first objective after landing for the rover is to secure the mother spacecraft landing through a characterization of the soil (regolith). Hence, in the nominal rover definition, several payloads are foreseen in order to contribute to the mission of the main spacecraft: to determine the origin of Martian moons

The MADMAX data set for visual‐inertial rover navigation on Mars

Planetary rovers increasingly rely on vision-based components for autonomous navigation and mapping. Developing and testing these components requires representative optical conditions, which can be achieved by either field testing at planetary analog sites on Earth or using prerecorded data sets from such locations. However, the availability of representative data is scarce and field testing in planetary analog sites requires a substantial financial investment and logistical overhead, and it entails the risk of damaging complex robotic systems. To address these issues, we use our compact human-portable DLR Sensor Unit for Planetary Exploration Rovers (SUPER) in the Moroccan desert to show resource-efficient field testing and make the resulting Morocco-Acquired data set of Mars-Analog eXploration (MADMAX) publicly accessible. The data set consists of 36 different navigation experiments, captured at eight Mars analog sites of widely varying environmental conditions. Its longest trajectory covers 1.5 km and the combined trajectory length is 9.2 km. The data set contains time-stamped recordings from monochrome stereo cameras, a color camera, omnidirectional cameras in stereo configuration, and from an inertial measurement unit. Additionally, we provide the ground truth in position and orientation together with the associated uncertainties, obtained by a real-time kinematic-based algorithm that fuses the global navigation satellite system data of two body antennas. Finally, we run two state-of-the-art navigation algorithms, ORB-SLAM2 and VINS-mono, on our data to evaluate their accuracy and to provide a baseline, which can be used as a performance reference of accuracy and robustness for other navigation algorithms. The data set can be accessed at https://rmc.dlr.de/morocco2018