Mars Helicopter Research Articles

Situation Awareness of Mars helicopter based on YOLOv7

Situation awareness on Mars is indispensable for various downstream applications such as navigation and path planning, mapping and scientific discover. However, current Mars rover platform suffered from the absence of global information, leading to mission reduction and the failure of global planning. Compared to the rover, Mars helicopter is a new type of attempt for Mars exploration, which can provide a wide range view of scenes to well support the above missions. To this end, in this paper we proposed a novel learning-based situation awareness model for Mars helicopter. We modified the Yolov7 model by embedding a new channel attention on its head to improve the accuracy of detection. Besides, we designed a Tiny-Scale Detection Module (TSDM) to capture small or hidden rocks in complex Martian surface. To achieve further refinement and validate our proposal, we built an open-source synthetic dataset in air view. After extensive experiments, our model achieved excellent outperforms than the baseline model in our Mars dataset.

Enhancing Communication Link Predictions for Ingenuity Mars Helicopter Mission With the Parabolic Equation Method

Enhancing Communication Link Predictions for Ingenuity Mars Helicopter Mission With the Parabolic Equation Method

A Neuromorphic Vision-Based Measurement for Robust Relative Localization in Future Space Exploration Missions

Space exploration has witnessed revolutionary changes upon landing of the Perseverance Rover on the Martian surface and demonstrating the first flight beyond Earth by the Mars helicopter, Ingenuity. During their mission on Mars, Perseverance Rover and Ingenuity collaboratively explore the Martian surface, where Ingenuity scouts terrain information for rover’s safe traversability. Hence, determining the relative poses between both the platforms is of paramount importance for the success of this mission. Driven by this necessity, this work proposes a robust relative localization system based on a fusion of neuromorphic vision-based measurements (NVBMs) and inertial measurements. The emergence of neuromorphic vision triggered a paradigm shift in the computer vision community, due to its unique working principle delineated with asynchronous events triggered by variations of light intensities occurring in the scene. This implies that observations cannot be acquired in static scenes due to illumination invariance. To circumvent this limitation, high frequency active landmarks are inserted in the scene to guarantee consistent event firing. These landmarks are adopted as salient features to facilitate relative localization. A novel event-based landmark identification algorithm using Gaussian Mixture Models (GMM) is developed for matching the landmarks correspondences formulating our NVBMs. The NVBMs are fused with inertial measurements in proposed state estimators, landmark tracking Kalman filter (LTKF) and translation decoupled Kalman filter (TDKF) for landmark tracking and relative localization, respectively. The proposed system was tested in a variety of experiments and has outperformed state-of-the-art approaches in accuracy and range.

Onboard Science Instrument Autonomy for the Detection of Microscopy Biosignatures on the Ocean Worlds Life Surveyor

The quest to find extraterrestrial life is a critical scientific endeavor with civilization-level implications. Icy moons in our solar system are promising targets for exploration because their liquid oceans make them potential habitats for microscopic life. However, the lack of a precise definition of life poses a fundamental challenge to formulating detection strategies. To increase the chances of unambiguous detection, a suite of complementary instruments must sample multiple independent biosignatures (e.g., composition, motility/behavior, and visible structure). Such an instrument suite could generate 10,000× more raw data than is possible to transmit from distant ocean worlds like Enceladus or Europa. To address this bandwidth limitation, Onboard Science Instrument Autonomy (OSIA) is an emerging discipline of flight systems capable of evaluating, summarizing, and prioritizing observational instrument data to maximize science return. We describe two OSIA implementations developed as part of the Ocean World Life Surveyor (OWLS) prototype instrument suite at the Jet Propulsion Laboratory. The first identifies life-like motion in digital holographic microscopy videos, and the second identifies cellular structure and composition via innate and dye-induced fluorescence. Flight-like requirements and computational constraints were used to lower barriers to infusion, similar to those available on the Mars helicopter, “Ingenuity.” We evaluated the OSIA's performance using simulated and laboratory data and conducted a live field test at the hypersaline Mono Lake planetary analog site. Our study demonstrates the potential of OSIA for enabling biosignature detection and provides insights and lessons learned for future mission concepts aimed at exploring the outer solar system.

Machine Learning Assisted Prediction of Airfoil Lift-to-Drag Characteristics for Mars Helicopter

The aerodynamic properties of rotor systems operating within low Reynolds number flow field conditions are profoundly influenced by their geometric and flight parameters. Precise estimation of optimal airfoil parameters at different angles of attack is indispensable for enhancing these aerodynamic properties. This study presents a technique for optimizing the airfoil parameters of a Mars helicopter by employing machine learning methods in conjunction with computational fluid dynamics (CFD) simulations, thereby circumventing the need for expensive experiments and simulations. The effectiveness of diverse machine learning algorithms for prediction is evaluated, and the resultant models are utilized for airfoil optimization. Ultimately, the aerodynamic properties of the optimized airfoil are experimentally validated. The experimental findings exhibit agreement with the simulated predictions, indicating the successful optimization of the aerodynamic properties. This research offers valuable insights into the influence of airfoil parameters on the aerodynamic properties of the Mars helicopter, along with guidance for airfoil optimization.

Flight dynamics modeling and analysis for a Mars helicopter

Flight dynamics modeling for the Mars helicopter faces great challenges. Aerodynamic modeling of coaxial rotor with high confidence and high computational efficiency is a major difficulty for the field. This paper builds an aerodynamic model of coaxial rotor in the extremely thin Martian atmosphere using the viscous vortex particle method. The aerodynamic forces and flow characteristics of rigid coaxial rotor are computed and analyzed. Meanwhile, a high fidelity aerodynamic surrogate model is built to improve the computational efficiency of the flight dynamics model. Results in this paper reveal that rigid coaxial rotor can bring the Mars helicopter sufficient controllability but result in obvious instability and control couplings in forward flight. This highlights the great differences in flight dynamics characteristics compared with conventional helicopters on Earth.

Towards energy efficient autonomous exploration of Mars lava tube with a Martian coaxial quadrotor

Mapping and exploration of a Martian terrain with an aerial vehicle has become an emerging research direction, since the successful flight demonstration of the Mars helicopter Ingenuity. Although the autonomy and navigation capability of the state of the art Mars helicopter has proven to be efficient in an open environment, the next area of interest for exploration on Mars are caves or ancient lava tube like environments, especially towards the never-ending search of life on other planets. This article presents an autonomous exploration mission based on a modified frontier approach along with a risk aware planning and integrated collision avoidance scheme with a special focus on energy aspects of a custom designed Mars Coaxial Quadrotor (MCQ) in a Martian simulated lava tube. One of the biggest novelties of the article stems from addressing the exploration capability, while rapidly exploring in local areas and intelligently global re-positioning of the MCQ when reaching dead ends in order to efficiently use the battery based consumed energy, while increasing the volume of the exploration. The proposed novel algorithm for the Martian exploration is able to select the next way point of interest, such that the MCQ keeps its heading towards the local exploration direction where it will find maximum information about the surroundings. The proposed three layer cost based global re-position point selection assists in rapidly redirecting the MCQ to previously partially seen areas that could lead to more unexplored part of the lava tube. The Martian fully simulated mission presented in this article takes into consideration the fidelity of physics of Mars condition in terms of thin atmosphere, low surface pressure and low gravity of the planet, while proves the efficiency of the proposed scheme in exploring an area that is particularly challenging due to the subterranean-like environment. The proposed exploration-planning framework is also validated in simulation by comparing it against the graph based exploration planner. Intensive simulations with true Mars conditions are carried out in order to validate and benchmark our approach in a utmost realistic Mars lava tube exploration scenario using a Mars Coaxial Quadrotor.

Visual Loop Closure Detection for a Future Mars Science Helicopter

Future Mars Rotorcrafts will require the ability to precisely navigate to previously visited locations in order to return to a safe landing site or execute precise scientific measurements, such as sample acquisition or targeted sensing. To enable a future Mars Science Helicopter to perform in-flight loop closures, we present an on-board visual loop closure detection system based on a Bag-of-Words (BoW) approach that is efficient enough to run in real-time on the anticipated computationally constrained flight avionics. Our system establishes image-to-image associations between incoming images of a downward-looking navigation camera and previously observed geo-tagged keyframes stored in a database. The system extracts ORB features which are quantized into a BoW histogram using a custom one million words hierarchical vocabulary, trained on synthetic images from a Mars simulation. An efficient database query using an inverted index produces a set of candidate frames which we check for geometrical consistency. For efficient feature matching, we leverage the vocabulary to perform fast approximate nearest neighbor search. The geometrical check accepts loop closure pairs whose essential matrix is supported by a minimum number of feature matches, which are pre-selected based on a rotational consistency check. The vocabulary and the methods used for the geometrical consistency checks were chosen to maximize the performance while allowing single-thread real-time execution on a computationally constrained embedded processor. We demonstrate and evaluate the proposed system both on simulated and real-world data, including flight data from the Mars Helicopter <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Ingenuity</i> .

Mars Helicopter Exceeds Expectations

Mars Helicopter Exceeds Expectations

Low-density multi-fan wind tunnel design and testing for the Ingenuity Mars Helicopter

Low-density multi-fan wind tunnel design and testing for the Ingenuity Mars Helicopter

Range-Visual-Inertial Odometry: Scale Observability Without Excitation

Traveling at constant velocity is the most efficient trajectory for most robotics applications. Unfortunately without accelerometer excitation, monocular Visual-Inertial Odometry (VIO) cannot observe scale and suffers severe error drift. This was the main motivation for incorporating a 1D laser range finder in the navigation system for NASA's Ingenuity Mars Helicopter. However, Ingenuity's simplified approach was limited to flat terrains. The current paper introduces a novel range measurement update model based on using facet constraints. The resulting range-VIO approach is no longer limited to flat scenes, but extends to any arbitrary structure for generic robotic applications. An important theoretical result shows that scale is no longer in the right nullspace of the observability matrix for zero or constant acceleration motion. In practical terms, this means that scale becomes observable under constant-velocity motion, which enables simple and robust autonomous operations over arbitrary terrain. Due to the small range finder footprint, range-VIO retains the minimal size, weight, and power attributes of VIO, with similar runtime. The benefits are evaluated on real flight data representative of common aerial robotics scenarios. Robustness is demonstrated using indoor stress data and fullstate ground truth. We release our software framework, called xVIO, as open source.

High-Fidelity Aeromechanical Analysis of Coaxial Mars Helicopter

A high-fidelity coupled computational fluid dynamics and comprehensive analysis solver is developed for helicopter flight on Mars. The objectives are accurate prediction of flight loads and fundamental understanding of Martian aeromechanics. Performance, structural loads, pitch link loads, rotor wake, and interrotor blade separation are studied for hingeless and flap articulated coaxial rotors. In the absence of any validation data, pressure chamber tests are carried out at Mars-like conditions on a single rotor in hover. The data provided an elementary assessment of rotor behavior and a baseline for model validation. Predictions of the high-fidelity solver are also compared with a lower-fidelity lifting-line comprehensive analysis. It is generally concluded that lower-fidelity tools are not adequate for capturing the complex flow phenomena encountered on Mars. A motion and loads comparison of two fundamental hub types revealed that 1) an articulated hub has similar interrotor blade separation as hingeless on Mars, 2) a hingeless hub experiences only marginally higher (6–7%) flap bending moments, and 3) an articulated hub can lower steady pitch link loads (by an order of magnitude) at a marginal expense of oscillatory loads, 15% higher.

Will the Mars Helicopter Induce Local Martian Atmospheric Breakdown?

Abstract Any rotorcraft on Mars will fly in a low-pressure and dusty environment. It is well known that helicopters on Earth become highly charged due, in part, to triboelectric effects when flying in sandy conditions. We consider the possibility that the Mars Helicopter Scout (MHS), called Ingenuity, flying at Mars as part of the Mars 2020 Perseverance mission, will also become charged due to grain-rotor triboelectric interactions. Given the low Martian atmospheric pressure of ∼5 Torr, the tribocharge on the blade could become intense enough to stimulate gas breakdown near the surface of the rotorcraft. We modeled the grain–blade interaction as a line of current that forms along the blade edge in the region where grain–blade contacts are the greatest. This current then spreads throughout the connected quasi-conductive regions of the rotorcraft. Charge builds up on the craft, and the dissipative pathway to remove charge is back into the atmosphere. We find that for blade tribocharging currents that form in an ambient atmospheric dust load, system current balance and charge dissipation can be accomplished via the nominal atmospheric conductive currents. However, at takeoff and landing, the rotorcraft could be in a rotor-created particulate cloud, leading to local atmospheric electrical breakdown near the rotorcraft. We especially note that the atmospheric currents in the breakdown are not large enough to create any hazard to Ingenuity itself, but Ingenuity operations can be considered a unique experiment that provides a test of the electrical properties of the Martian near-surface atmosphere.

Scalable information-theoretic path planning for a rover-helicopter team in uncertain environments

Mission-critical exploration of uncertain environments requires reliable and robust mechanisms for achieving information gain. Typical measures of information gain such as Shannon entropy and KL divergence are unable to distinguish between different bimodal probability distributions or introduce bias toward one mode of a bimodal probability distribution. The use of a standard deviation (SD) metric reduces bias while retaining the ability to distinguish between higher and lower risk distributions. Areas of high SD can be safely explored through observation with an autonomous Mars Helicopter allowing safer and faster path plans for ground-based rovers. First, this study presents a single-agent information-theoretic utility-based path planning method for a highly correlated uncertain environment. Then, an information-theoretic two-stage multiagent rapidly exploring random tree framework is presented, which guides Mars helicopter through regions of high SD to reduce uncertainty for the rover. In a Monte Carlo simulation, we compare our information-theoretic framework with a rover-only approach and a naive approach, in which the helicopter scouts ahead of the rover along its planned path. Finally, the model is demonstrated in a case study on the Jezero region of Mars. Results show that the information-theoretic helicopter improves the travel time for the rover on average when compared with the rover alone or with the helicopter scouting ahead along the rover’s initially planned route.

Scaling sediment mobilization beneath rotorcraft for Titan and Mars

Using rotorcraft to explore extraterrestrial bodies will allow future missions to explore terrain that is inaccessible to traditional lander/rover missions, and will enable spacecraft to explore much larger distances than previous missions. The upcoming Mars 2020 Rover mission will include the Mars Helicopter (named Ingenuity), a small ( < 2 kg) counter-rotating co-axial vehicle, which, if successful, will be the first rotorcraft to fly on a non-terrestrial body. The Dragonfly mission, recently selected through the NASA New Frontier’s program, is expected to fly a much larger vehicle on Titan ( ∼ 750 kg) arriving in the early 2030s. On Earth it is commonly observed that both sub-scale and full-scale rotorcraft can mobilize sediment, to varying degrees of magnitude, when a vehicle is operating over regolith. In order to determine the feasibility of performing sediment mobilization experiments (e.g. saltation investigations) beneath a rotorcraft through intentional sediment mobilization (due to the wake produced by the rotating rotors) for future missions, the scaling of aerodynamic and aeolian parameters should be accounted for. Furthermore, in an extreme case, this analysis can also be used as a low-fidelity method to begin to understand any potential risk associated with brownout (large-scale sediment mobilization due to the helicopter rotor wake) to the rotorcraft itself. In this work, a scaling analysis is presented that allows a vehicle designer to quickly investigate the magnitude of sediment mobilization beneath a rotorcraft, without requiring detailed CFD simulations. The analysis confirms that the upcoming Mars Helicopter and Dragonfly missions could be used for sediment mobilization experiments.

The Mars Helicopter Telecommunication Link: Antennas, Propagation, and Link Analysis

This article presents the progress in the development of the telecommunication subsystem for the Mars Helicopter. The antenna performance on the rover and the helicopter are assessed. An in-depth analysis of the link between the Mars Helicopter and the Mars 2020 (M2020) rover is presented in detail, including the impact of polarization loss, multipath, and antenna performance. The antenna designs and analyses are described as they play a critical role in the link assessment. The analysis is verified through a field test which included a proxy rover and helicopter with engineering model antennas.

Designing Mars Missions for the Utilization of Rotorcraft

Following the technical demonstration of the Mars Helicopter on the Mars 2020 mission, interest in further exploration of Mars utilizing rotorcraft is expected to increase. Previously, scientific exploration has been limited by the resolution of instruments on satellites and the terrain a rover can traverse. Rotorcraft enable exploration in previously inaccessible locations with increased efficiency compared to rovers and improved resolution (compared to satellites). This paper describes missions designed to utilize the unique capabilities of rotorcraft in order to advance the science performed extraterrestrially. For Mars this includes tasks such as determining if Mars ever supported life, understanding climate processes and history, determining the evolution of Martian geology, and preparing for human exploration. The missions fall into three general categories: rover assistance, sample collection, and data collection. Complimentary conceptvehicles are also discussed. This paper is meant to serve as a reference, resource, and starting point for the future exploration of Mars with rotorcraft.

Modeling and Identification of Hover Flight Dynamics for NASA’s Mars Helicopter

As part of the upcoming Mars 2020 rover mission, NASA is planning to include an autonomous helicopter to demonstrate the feasibility and utility of using helicopters for Mars exploration. Helicopter flight on Mars is challenging due to the extremely thin atmosphere, which is only partially offset by a reduction in gravity. This paper focuses on flight dynamics and controllability issues for the Mars Helicopter: in particular, the areas in which the dynamics differs from typical behavior on Earth. The paper discusses insights gained from modeling and simulation, as well as system identification performed with a test vehicle in the relevant atmospheric conditions, which culminated in the first demonstration of controlled helicopter flight in Martian atmospheric conditions in May 2016.

The Measure of: Mars Helicopter Scout (MHS)

The Measure of: Mars Helicopter Scout (MHS)

Improved Mars Helicopter Aerodynamic Rotor Model for Comprehensive Analyses

The Mars Helicopter is part of the NASA Mars 2020 rover mission scheduled to launch in July of 2020. Its goal is to demonstrate the viability and potential of heavier-than-air vehicles in the Martian atmosphere. The low density of the Martian atmosphere and the relatively small-scale rotor result in flows with very low Reynolds number, reducing the lifting force and lifting efficiency, respectively. This paper describes the generation of the improved Mars Helicopter aerodynamic rotor model. The goal is to generate a performance model for the Mars Helicopter rotor using a free wake analysis in CAMRADII. The improvements in the analysis are twofold and are expanded on from two prior publications. First, the fidelity of the simulations is increased by performing higher-order time-accurate OVERFLOW simulations allowing for higher-accuracy aerodynamic coefficients and a better understanding of the boundary-layer behavior. Second, a model is generated for the testing conditions in the 25-ft-diam Space Simulator at the Jet Propulsion Laboratory, allowing for better correlation of rotor performance figures. The higher temperatures in the experiment are expected to give conservative performance estimates, as they give rise to an increase in speed of sound and decrease in observed Reynolds numbers.