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Showing papers presented at "IEEE Aerospace Conference in 2020"


Proceedings ArticleDOI
07 Mar 2020
TL;DR: The first phase of the Gateway project as mentioned in this paper is focused on the launch of the Power and Propulsion Element (PPE) and the Habitation and Logistics Outpost (HALO), a minimal habitation capability.
Abstract: NASA is developing a two-phased approach to quickly return humans to the Moon and establish a sustainable presence in orbit and on the surface. The two phases run in parallel, and both have already begun, with selection of the first Gateway element, the Power and Propulsion Element, solicitation activities focused on an American-built, industry-provided Human Landing System, and discussions with industry and international partners about potential opportunities for collaboration. Phase 1 is driven exclusively by the administration's priority to land the first woman and the next man on the lunar South Pole by 2024. In this phase, NASA and its partners will develop and deploy two Gateway components: the Power and Propulsion Element (PPE) that will launch in 2022, and the Habitation and Logistics Outpost (HALO), a minimal habitation capability) that will launch in 2023. Both will launch on commercial rockets, as will Gateway logistics deliveries to outfit the ship and provide supplies for surface expeditions. This initial Gateway configuration represents the beginning of its capability buildup, and the primary components required to support the first human expedition to the lunar South Pole. NASA's baseline reference approach for human expeditions on the surface is for Human Landing Systems to aggregate and dock to the Gateway, then deploy to the lunar South Pole with two astronauts aboard. Phase 2 is focused on advancing the technologies that will foster a sustainable presence on and around the Moon - a lasting and productive presence enabled by reusable systems, access for a diverse body of contributing partners, and repeatable trips to multiple destinations across the lunar surface. In this Phase, we will advance sustainable systems to make surface expeditions more repeatable and affordable. While the Gateway is the first of its kind to be funded, the concept has been proposed for decades as a necessary and foundational capability for a sustainable return to the Moon, and a port for vehicles embarking to farther destinations. It supports every tenet of Space Policy Directive-1 and the infrastructure it provides is critical to an accelerated return to the Moon, and access to more parts of the Moon than ever before. The Gateway also provides a unique platform to conduct cross-discipline science. Science instruments, both internal and external to the Gateway, have the potential to reveal new findings in space science, Earth science, and biological research data from deep space. Additionally, the broad science community will be able to utilize the communications and data relay capabilities of the Gateway, beginning with the PPE in Phase 1. This paper will outline the cross-discipline activities NASA is currently conducting, and those the agency anticipates conducting in the future to successfully implement Phases 1 and 2 in the lunar vicinity, all while preparing for humanity's next giant leap: Mars.

102 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: Team CoSTAR's results in the first phase of the DARPA Subterranean Challenge are described, focusing on supervised autonomy of a multi-robot team under severe communication constraints, and the design and initial results obtained from field test campaigns conducted in various tunnel-like environments, leading to the competition.
Abstract: The importance of autonomy in robotics is magnified when the robots need to be deployed and operated in areas that are too dangerous or not accessible for humans, ranging from disaster areas (to assist in emergency situations) to Mars exploration (to uncover the mystery of our neighboring planet). The DARPA Subterranean (SubT) Challenge presents a great opportunity and a formidable robotics challenge to foster such technological advancement for operations in extreme and underground environments. Robot teams are expected to rapidly map, navigate, and search underground environments including natural cave networks, tunnel systems, and urban underground infrastructure. Subterranean environments pose significant challenges for manned and unmanned operations due to limited situational awareness. In the first phase of the DARPA Subterranean Challenge (held in August 2019; targeting underground tunnels and mines), Team CoSTAR, led by NASA JPL, placed second among 11 teams across the world, accurately mapping several kilometers of two mine systems and localizing 17 target objects in the course of four one-hour missions. While the main goal of Team CoSTAR at the end of this three-year challenge (August 2021) is a fully autonomous robotic solution, this paper describes Team CoSTAR's results in the first phase of the challenge (August 2019), focusing on supervised autonomy of a multi-robot team under severe communication constraints. This paper also presents the design and initial results obtained from field test campaigns conducted in various tunnel-like environments, leading to the competition.

41 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: The Earth Surface Mineral Dust Source Investigation (EMIT) project as mentioned in this paper uses visible to short wavelength infrared imaging spectroscopy to determine the mineral composition of the arid land dust source regions of the Earth to advance our knowledge of the radiative forcing effect of these aerosols.
Abstract: The Earth Surface Mineral Dust Source Investigation, EMIT, is planned to operate from the International Space Station starting no earlier than the fall of 2021. EMIT will use visible to short wavelength infrared imaging spectroscopy to determine the mineral composition of the arid land dust source regions of the Earth to advance our knowledge of the radiative forcing effect of these aerosols. Mineral dust emitted into the atmosphere under high wind conditions is an element of the Earth system with many impacts to the Earth's energy balance, atmosphere, surface, and oceans. The Earth's mineral dust cycle with source, transport, and deposition phases are studied with advanced Earth System Models. Because the chemical composition, optical and surface properties of soil particles vary strongly with the mineral composition of the source, these models require knowledge of surface soil mineral dust source composition to accurately understand dust impacts on the Earth system now and in the future. At present, compositional knowledge of the Earth's mineral dust source regions from existing data sets is uncertain as a result of limited measurements. EMIT will use spectroscopically-derived surface mineral composition to update the prescribed boundary conditions for state-of-the-art Earth System Models. The EMIT-initialized models will be used to investigate the impact of direct radiative forcing in the Earth system that depends strongly on the composition of the mineral dust aerosols emitted into the atmosphere. These new measurements and related products will be used to address the EMIT science objectives and made available to the science community for additional investigations. An overview of the EMIT science, development, and mission is presented in this paper.

39 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: NISAR data will clarify spatially and temporally complex phenomena, including ecosystem disturbances, ice sheet collapse, and natural hazards including earthquakes, tsunamis, volcanoes, and landslides, and provide societally relevant data that will enable better protection of life and property.
Abstract: NISARis a multi-disciplinary Earth-observing radar mission that makes global measurements of land surface changes that will greatly improve Earth system models. NISAR data will clarify spatially and temporally complex phenomena, including ecosystem disturbances, ice sheet collapse, and natural hazards including earthquakes, tsunamis, volcanoes, and landslides. It provides societally relevant data that will enable better protection of life and property. The mission, a NASA-ISRO partnership, uses two fully polarimetric SARs, one at L-band (L-SAR) and one at S-band (S-SAR), in exact repeating orbits every 12 days that allows interferometric combination of data on repeated passes. NASA provides the L-SAR; a shared deployable reflector; an engineering payload that supports mission-specific data handling, navigation and communication functions; science observation planning and L-SAR data processing. ISRO provides the S-SAR, spacecraft, launch vehicle, satellite operations, and S-SAR data processing. The mission will be launched from the Satish Dhawan Space Centre, Sriharikota, India. Mission development has addressed many unique challenges and incorporates many “firsts” for a jointly-developed free-flyer radar science mission

38 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: In this paper, the authors describe mobility trends over the first 21.3km of the Mars Science Laboratory (MSL) mission, operational aspects of the mobility fault protection, and risk mitigation strategies that will support continued mobility success for the remainder of the mission.
Abstract: NASA's Mars Science Laboratory (MSL) mission landed the Curiosity rover on Mars on August 6, 2012. As of August 6, 2019 (sol 2488), Curiosity has driven 21,318.5 meters over a variety of terrain types and slopes, employing multiple drive modes with varying amounts of onboard autonomy. Curiosity's drive distances each sol have ranged from its shortest drive of 2.6 centimeters to its longest drive of 142.5 meters, with an average drive distance of 28.9 meters. Real-time human intervention during Curiosity drives on Mars is not possible due to the latency in uplinking commands and downlinking telemetry, so the operations team relies on the rover's flight software to prevent an unsafe state during driving. Over the first seven years of the mission, Curiosity has attempted 738 drives. While 622 drives have completed successfully, 116 drives were prevented or stopped early by the rover's fault protection software. The primary risks to mobility success have been wheel wear, wheel entrapment, progressive wheel sinkage (which can lead to rover embedding), and terrain interactions or hardware or cabling failures that result in an inability to command one or more steer or drive actuators. In this paper, we describe mobility trends over the first 21.3km of the mission, operational aspects of the mobility fault protection, and risk mitigation strategies that will support continued mobility success for the remainder of the mission.

36 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: A new class of Micro Aerial Vehicles are equipped with the ability to localize and map in subterranean settings, explore unknown mine environments on their own, and perform detection and localization of objects of interest for the purposes of mine rescue.
Abstract: In this paper we present a comprehensive solution for autonomous underground mine rescue using aerial robots. In particular, a new class of Micro Aerial Vehicles are equipped with the ability to localize and map in subterranean settings, explore unknown mine environments on their own, and perform detection and localization of objects of interest for the purposes of mine rescue (i.e., “human survivors” and associated objects such as “backpacks”, “smartphones” or “tools”). For the purposes of GPS-denied localization and mapping in the visually-degraded underground environments (e.g., a smoke-filled mine during an accident) the solution relies on the fusion of LiDAR data with thermal vision frames and inertial cues. Autonomous exploration is enabled through a graph-based search algorithm and an online volumetric representation of the environment. Object search is then enabled through a deep learning-based classifier, while the associated location is queried using the online reconstructed map. The complete software framework runs onboard the aerial robots utilizing the integrated embedded processing resources. The overall system is extensively evaluated in real-life deployments in underground mines.

36 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: This paper provides a high-level description of an extensible and scalable lunar communications and navigation architecture, known as LunaNet, a services network to enable lunar operations.
Abstract: NASA has set the ambitious goal of establishing a sustainable human presence on the Moon. Diverse commercial and international partners are engaged in this effort to catalyze scientific discovery, lunar resource utilization and economic development on both the Earth and at the Moon. Lunar development will serve as a critical proving ground for deeper exploration into the solar system. Space communications and navigation infrastructure will play an integral part in realizing this goal. This paper provides a high-level description of an extensible and scalable lunar communications and navigation architecture, known as LunaNet. LunaNet is a services network to enable lunar operations. Three LunaNet service types are defined: networking services, position, navigation and timing services, and science utilization services. The LunaNet architecture encompasses a wide variety of topology implementations, including surface and orbiting provider nodes. In this paper several systems engineering considerations within the service architecture are highlighted. Additionally, several alternative LunaNet instantiations are presented. Extensibility of the LunaNet architecture to the solar system internet is discussed.

35 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: This paper compares some of the recently proposed dynamic resource allocation algorithms under realistic operational assumptions, addressing a specific problem in which power needs to be assigned to each beam in a multibeam High Throughput Satellite (HTS).
Abstract: Automating resource management strategies is a key priority in the satellite communications industry. The future landscape of the market will be changed by a substantial increase of data demand and the introduction of highly flexible communications payloads able to operate and reconfigure hundreds or even thousands of beams in orbit. This increase in dimensionality and complexity puts the spotlight on Artificial Intelligence-based dynamic algorithms to optimally make resource allocation decisions, as opposed to previous fixed policies. Although multiple approaches have been proposed in the recent years, most of the analyses have been conducted under assumptions that do not entirely reflect operation scenarios. Furthermore, little work has been done in thoroughly comparing the performance of different algorithms. In this paper we compare some of the recently proposed dynamic resource allocation algorithms under realistic operational assumptions, addressing a specific problem in which power needs to be assigned to each beam in a multibeam High Throughput Satellite (HTS). We focus on Genetic Algorithms, Simulated Annealing, Particle Swarm Optimization, Deep Reinforcement Learning, and hybrid approaches. Our multibeam operation scenario uses demand data provided by a satellite operator, a full radio-frequency chain model, and a set of hardware and time constraints present during the operation of a HTS. We compare these algorithms focusing on the following characteristics: time convergence, continuous operability, scalability, and robustness. We evaluate the performance of the algorithms against different test cases and make recommendations on the approaches that are likely to work better in each context.

30 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: This paper is to provide the latest snapshot of the project with broad and high-level description of every capability that the project is developing, including scientific scene interpretation, vision-based traversability assessment, resource-aware path planning, information-theoretic path planner, and on-board strategic path planning.
Abstract: MAARS (Machine leaning-based Analytics for Automated Rover Systems) is an ongoing JPL effort to bring the latest self-driving technologies to Mars, Moon, and beyond. The ongoing AI revolution here on Earth is finally propagating to the red planet as the High Performance Spaceflight Computing (HPSC) and commercial off-the-shelf (COTS) system-on-a-chip (SoC), such as Qualcomm's Snapdragon, become available to rovers. In this three year project, we are developing, implementing, and benchmarking a wide range of autonomy algorithms that would significantly enhance the productivity and safety of planetary rover missions. This paper is to provide the latest snapshot of the project with broad and high-level description of every capability that we are developing, including scientific scene interpretation, vision-based traversability assessment, resource-aware path planning, information-theoretic path planning, on-board strategic path planning, and on-board optimal kinematic settling for accurate collision checking. All of the onboard software capabilities will be integrated into JPL's Athena test rover using ROS (Robot Operating System).

29 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: A hybrid aerial/ground vehicle that combines the capabilities of both types of vehicles to enable multi-modal mobility in diverse and challenging environments, a lower cost of transport compared to purely aerial vehicles, increased payload capacity, and a design that is more robust to collisions and physical interaction within potentially cluttered and narrow spaces is presented.
Abstract: Aerial robots show promise for increased capabilities in exploring unstructured and challenging environments. However, they are limited by payload capacity, flight times, and susceptibility to damage in case of collision. On the other hand, ground robots are able to carry larger payloads and have a lower cost of transport, at the price of limited mobility over challenging terrain. This paper presents a hybrid aerial/ground vehicle that combines the capabilities of both types of vehicles to enable multi-modal mobility in diverse and challenging environments, a lower cost of transport compared to purely aerial vehicles, increased payload capacity, and a design that is more robust to collisions and physical interaction within potentially cluttered and narrow spaces. The design consists of a UAV with four independently actuated spherical wheels which, in addition to providing traction for ground mobility, protect the propellers in collision. In comparison to hybrid vehicles with passive wheels presented in other designs, actuated wheels mitigates perception degradation in dusty environments caused by downwash from thrusting close to the ground. In addition, the integration of an end-to-end autonomy stack is presented which enables the control, planning, and autonomous navigation of the hybrid vehicle in unknown environments. The controls framework employs a geometric tracking controller for aerial trajectories and a cascaded position and velocity controller for ground mobility. We leverage motion primitives to locally plan collision-free paths and a differential flatness mapping to generate kinodynamically feasible trajectories for both terrestrial and aerial modalities in a unified manner. Lastly, we utilize a grid based A* search and probabilistic 3D mapping based on octrees to plan geometric aerial/ground paths to a goal. With this framework, we hope to demonstrate the capabilities of this hybrid aerial/ground vehicle in challenging unknown environments and improved energy efficiency for hybrid mobility over purely flying.

26 citations


Proceedings ArticleDOI
07 Mar 2020
TL;DR: This work presents an implementation of a new metaheuristic algorithm based on Particle Swarm Optimization (PSO) to solve the joint power and bandwidth allocation problem and shows that the hybrid implementation outperforms a GA-only algorithm for low run-time executions (10-second executions).
Abstract: In recent years, communications satellites' payloads have been evolving from static to highly flexible components. Modern satellites are able to provide four orders of magnitude higher throughput than their predecessors forty years ago, going from a few Mbps to several hundreds of Gbps. This enhancement in performance is aligned with an increasing highly-variable demand. In order to dynamically and efficiently manage the satellite's resources, an automatic tool is needed. This work presents an implementation of a new metaheuristic algorithm based on Particle Swarm Optimization (PSO) to solve the joint power and bandwidth allocation problem. We formulate this problem as a multi-objective approach that considers the different constraints of a communication satellite system. The evaluation function corresponds to a full-RF link budget model that accounts for adaptive coding and modulation techniques as well as multiple types of losses. We benchmark the algorithm using a realistic traffic model provided by a satellite communications operator and under time restrictions present in an operational environment. The results show a fast convergence of the PSO algorithm, reaching an admissible solution in seconds. However, the PSO tends to get stuck in local optima and often fails to reach the global optimum. This motivates the creation of a hybrid metaheuristic combining the presented PSO with a Genetic Algorithm (GA). We show that this approach dominates the PSO-only both in terms of power consumption and service rate. Furthermore, we also show that the hybrid implementation outperforms a GA-only algorithm for low run-time executions (10-second executions). The hybrid provides up to an 85% power reduction and up to 10% better service rate in this case.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: An autonomous Sequential Decision Process (SDP) for sUAV navigation that incorporates target detection uncertainty from vision-based cameras is presented, modelled as a Partially Observable Markov Decision process (POMDP) and solved online using the Adaptive Belief Tree (ABT) algorithm.
Abstract: The use of Small Unmanned Aerial Vehicles (sUAVs) has grown exponentially owing to an increasing number of autonomous capabilities. Automated functions include the return to home at critical energy levels, collision avoidance, take-off and landing, and target tracking. However, sUAVs applications in real-world and time-critical scenarios, such as Search and Rescue (SAR) is still limited. In SAR applications, the overarching aim of autonomous sUAV navigation is the quick localisation, identification and quantification of victims to prioritise emergency response in affected zones. Traditionally, sUAV pilots are exposed to prolonged use of visual systems to interact with the environment, which causes fatigue and sensory overloads. Nevertheless, the search for victims onboard a sUAV is challenging because of noise in the data, low image resolution, illumination conditions, and partial (or full) occlusion between the victims and surrounding structures. This paper presents an autonomous Sequential Decision Process (SDP) for sUAV navigation that incorporates target detection uncertainty from vision-based cameras. The SDP is modelled as a Partially Observable Markov Decision Process (POMDP) and solved online using the Adaptive Belief Tree (ABT) algorithm. In particular, a detailed model of target detection uncertainty from deep learning-based models is shown. The presented formulation is tested under Software in the Loop (SITL) through Gazebo, Robot Operating System (ROS), and PX4 firmware. A Hardware in the Loop (HITL) implementation is also presented using an Intel Myriad Vision Processing Unit (VPU) device and ROS. Tests are conducted in a simulated SAR GPS-denied scenario, aimed to find a person at different levels of location and pose uncertainty.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: An autonomous navigation system suitable for supporting a future Mars Science Helicopter concept, and a novel range update model to constrain visual-inertial scale drift in the absence of motion excitation using a single-point static laser range finder.
Abstract: This paper introduces an autonomous navigation system suitable for supporting a future Mars Science Helicopter concept. This mission concept requires low-drift localization to reach science targets far apart from each other on the surface of Mars. Our modular state estimator achieves this through range, solar and Visual-Inertial Odometry (VIO). We propose a novel range update model to constrain visual-inertial scale drift in the absence of motion excitation using a single-point static laser range finder, that is designed to work over unknown terrain topography. We also develop a sun sensor measurement model to constrain VIO yaw drift. Solar VIO performance is evaluated in a simulation environment in a Monte Carlo analysis. Range-VIO is demonstrated in flight in real time on 1 core of a Qualcomm Snapdragon 820 processor, which is the successor of the NASA's Mars Helicopter flight processor.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: In this article, the status of the recent research on the cryogenic temperature behavior of Si semiconductor devices, wide bandgap semiconductor device, passive components, and power converter topologies is reviewed.
Abstract: The design considerations for power converters operating at room or at ultra-low temperatures are the same in terms of power density, reliability, and efficiency. In order to design power converters at cryogenic temperatures, the passive and active components should be carefully selected. Understanding the behavior of the components at cryogenic temperatures leads to power converter systems that have many superior advantages such as high power density (reduced size and volume), higher efficiency (reduced system losses), and even increased system reliability. This paper reviews the status of the recent research on the cryogenic temperature behavior of Si semiconductor devices, wide bandgap semiconductor devices, passive components, and power converter topologies.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: A generalized trajectory for in-time monitoring and prediction of autonomous UAVs using GPS measurements and critical challenges related to uncertainty quantification in trajectory prognosis for autonomous vehicles are identified and potential solutions are discussed.
Abstract: The expected increase of UAV operation in the next decade in areas of on-demand delivery, medical transportation services, law enforcement, traffic surveillance and several others pose potential risks to the low-altitude airspace above densely populated areas. Safety assessment of airspace demands the need for novel UAV traffic management frameworks for regulation and tracking of vehicles. Particularly for low-altitude UAV operations, quality of GPS measurements used for guidance, navigation, and control, is often compromised by loss of communication link caused by presence of trees or tall buildings in proximity to the UAV flight path. Inaccurate GPS measurements may yield unreliable monitoring and inaccurate prognosis of vehicle components such as remaining battery life and other safety metrics that rely on future expected trajectory of the UAV. This work therefore proposes a generalized trajectory for in-time monitoring and prediction of autonomous UAVs using GPS measurements. Firstly, a smooth 4D trajectory generation technique is presented using a series of waypoint locations with associated expected times-of-arrival based on B-spline curves. Initial uncertainty in the vehicle's expected cruise velocity is propagated through the trajectory to compute confidence intervals along the entire flight trajectory using error interval propagation approach. Further, the generated planned trajectory is considered as the prior knowledge that is updated during the UAV flight with incoming GPS measurements in order to refine its current location estimates and corresponding kinematic profiles. The estimation of the vehicle position is defined in a state-space representation such that the position at a future time step is derived from the position and velocity at the current time step and expected velocity at the future time step. A linear Bayesian filtering algorithm is employed to efficiently refine position estimation from noisy GPS measurements and update the confidence intervals. Further, a dynamic re-planning strategy is implemented to incorporate unexpected detour or delay scenarios. Finally, critical challenges related to uncertainty quantification in trajectory prognosis for autonomous vehicles are identified, and potential solutions are discussed at the end of the paper. The entire monitoring framework is demonstrated on real UAV flight experiments conducted at the NASA Langley Research Center.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: This paper proposes a methodology to accelerate SCP-based algorithms through warm-starting, leveraging a dataset of expert trajectories from GuSTO and devise a neural-network-based approach to predict a locally optimal state and control trajectory, which is used to warm-start the SCP algorithm.
Abstract: Sequential convex programming (SCP) has recently emerged as an effective tool to quickly compute locally optimal trajectories for robotic and aerospace systems alike, even when initialized with an unfeasible trajectory. In this paper, by focusing on the Guaranteed Sequential Trajectory Optimization (GuSTO) algorithm, we propose a methodology to accelerate SCP-based algorithms through warm-starting. Specifically, leveraging a dataset of expert trajectories from GuSTO, we devise a neural-network-based approach to predict a locally optimal state and control trajectory, which is used to warm-start the SCP algorithm. This approach allows one to retain all the theoretical guarantees of GuSTO while simultaneously taking advantage of the fast execution of the neural network and reducing the time and number of iterations required for GuSTO to converge. The result is a faster and theoretically guaranteed trajectory optimization algorithm.

Proceedings ArticleDOI
01 Mar 2020
TL;DR: This paper presents the first experimental analysis of the feasibility and human operator performance of telemanipulation with an Earth-to-Moon like delay of 3s, and the results are highly promising.
Abstract: The international space agencies plan to implement orbiting space stations around celestial bodies as moon or Mars in the near future. Autonomous robots will be assigned with exploration tasks and the building of structures as habitats. A teleoperator interface will be available in the orbiter to assure the possibility of direct control of the robots located on the celestial body as a fallback, in case an autonomous functionality fails. Communication links will be comparable to the ones between the International Space Station and earth, reaching from direct S-band communication, to communication via geostationary relay satellites in a Ku-Forward link. Since the planned Gateway orbiting the moon will not be manned throughout the year, further interfaces have to be established with which the robots can be controlled from earth. An available laser link to the moon provides a high-bandwidth communication with 2.6s roundtrip-delay, which currently allows for supervised control, for example via a tablet interface. Current advances in control theory can achieve stable and high performance kinesthetic feedback in bilateral telemanipulation at delays above 1s. This paper presents the first experimental analysis of the feasibility and human operator performance of telemanipulation with an Earth-to-Moon like delay of 3s. In light of the fact that several technologies such as visual augmentation and shared control can be integrated in addition, the results are highly promising.

Proceedings ArticleDOI
01 Mar 2020
TL;DR: In this paper, the authors developed an energy model to determine the feasibility of developing a mining base on the Moon based on water and metal mining and showed that automation and robotics is the key to making such a base technologically feasible.
Abstract: There is growing interest in expanding beyond space exploration and pursuing the dream of living and working in space. The next critical step towards living and working in space requires kick-starting a space economy. One important challenge with this space-economy is ensuring the ready supply and low-cost availability of raw materials. The escape delta-v of 11.2 km/s from Earth makes transportation of materials from Earth very costly. Transporting materials from the Moon takes 2.4 km/s and from Mars 5.0 km/s. Based on these factors, the Moon and Mars can become colonies to export material into this space economy. One critical question is what are the resources required to sustain a space economy? Water has been identified as a critical resource both to sustain human-life but also for use in propulsion, attitude-control, power, thermal storage and radiation protection systems. Water may be obtained off-world through In-Situ Resource Utilization (ISRU) in the course of human or robotic space exploration. The Moon is also rich in iron, titanium and silicon. Based upon these important findings, we plan on developing an energy model to determine the feasibility of developing a mining base on the Moon. This mining base mines and principally exports water, titanium and steel. The moon has been selected, as there are significant reserves of water known to exists at the permanently shadowed crater regions and there are significant sources of titanium and iron throughout the Moon's surface. Our designs for a mining base utilize renewable energy sources namely photovoltaics and solar-thermal concentrators to provide power to construct the base, keep it operational and export water and other resources using a Mass Driver. However, the site where large quantities of water are present lack sunlight and hence the water needs to be transported using rail from the southern region to base located at mid latitude. Using the energy model developed, we will determine the energy per Earth-day to export 100 tons each of water, titanium and low-grade steel into Lunar escape velocity and to the Earth-Moon Lagrange points. Our study of water and metal mining on the Moon found the key to keeping the mining base efficient is to make it robotic. Teams of robots (consisting of 300 infrastructure robots) would be used to construct the entire base using locally available resources and fully operate the base. This would decrease energy needs by 15-folds. Furthermore, the base can be built 15-times faster using robotics and 3D printing. This shows that automation and robotics is the key to making such a base technologically feasible. The Moon is a lot closer to Earth than Mars and the prospect of having a greater impact on the space economy cannot be stressed. Our study intends to determine the cost-benefit analysis of lunar resource mining.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: An integrated motion planning methodology that is a) fuel-efficient to ensure extended operation time and b) computationally-tractable to make possible on-board re-planning for improved exploration is presented.
Abstract: This paper addresses the problem of how to plan optimal motion for a swarm of on-orbit servicing (OOS) small-spacecraft remotely inspecting a non-cooperative client spacecraft in Earth orbit. With the goal being to maximize the information gathered from the coordinated inspection, we present an integrated motion planning methodology that is a) fuel-efficient to ensure extended operation time and b) computationally-tractable to make possible on-board re-planning for improved exploration. Our method is decoupled into first offline selection of optimal orbits, followed by online coordinated attitude planning. In the orbit selection stage, we numerically evaluate the upper and lower bounds of the information gain for a discretized set of passive relative orbits (PRO). The algorithm then sequentially assigns orbits to each spacecraft using greedy heuristics. For the attitude planning stage, we propose a dynamic programming (DP) based attitude planner capable of addressing vehicle and sensor constraints such as attitude control system specifications, sensor field of view, sensing duration, and sensing angle. Finally, we validate the performance of the proposed algorithms through simulation of a design reference mission involving 3U CubeSats inspecting a satellite in low Earth orbit.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: The potential of interaction methods supported by a combination of gaze-tracking and hand-tracking achieved via an additional sensor attached to the front of the VR headset are explored, with no need for the user to hold a controller.
Abstract: We present an immersive environment where Virtual Reality (VR) is used to visualize the performance of a fleet of aircraft engines. Our virtual environment uses 3D geometric computer-aided design (CAD) models of the engines paired with performance maps that characterize their nominal working condition. These maps plot pressure ratio and efficiency as a function of shaft speed and inlet flow capacity for the numerous engine sub-systems. Superimposed on these maps is the true performance of each engine, obtained through real-time sensors. In this bespoke virtual space, an engineer can rapidly analyze the health of different engine sub-systems across the fleet within seconds. One of the key elements of such a system is the selection of an appropriate interaction technique. In this paper we explore the potential of interaction methods supported by a combination of gaze-tracking and hand-tracking achieved via an additional sensor attached to the front of the VR headset, with no need for the user to hold a controller. We report on an observational study with a small number of domain-experts to identify usability problems, spot potential improvements, and gain insights into our design interaction capabilities. The study allows us to trim the design space and to guide further design efforts in this area. We also analyze qualitative feedback provided by the end-users and discuss the lessons learned during the design, implementation, verification and validation of the system.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: MMX (Martian Moons eXploration) is a robotic sample return mission of JAXA (Japan Aerospace Exploration Agency), CNES (Centre National d' Etudes Spatiales), and DLR (German Aerospace Center) with the launch planed for 2024 as mentioned in this paper.
Abstract: MMX (Martian Moons eXploration) is a robotic sample return mission of JAXA (Japan Aerospace Exploration Agency), CNES (Centre National d' Etudes Spatiales), and DLR (German Aerospace Center) with the launch planed for 2024. The mission aims to answer the question of the origin of Phobos and Deimos, which will also help to understand the material transport in the earliest period of our solar system, and of how was water brought to Earth. Besides JAXA's MMX mothership, which is responsible for sampling and sample return to Earth, a small rover which is built by CNES and DLR to land on Phobos for in-situ measurements, similar to MASCOT (Mobile Asteroid Surface Scout) on Ryugu. The MMX rover is a four-wheel driven autonomous system with a size of 41 cm × 37 cm × 30 cm and a weight of approximately 25 kg. Multiple science instruments and cameras are integrated in the rover body. The rover body has the form of a rectangular box. Attached at the sides are four legs with one wheel per leg. When the rover is detached from the mothership, the legs are folded together at the side of the rover body. When the rover has landed passively (no parachute or braking rockets) on Phobos, the legs are autonomously maneuvered to bring the rover in an upright orientation. One Phobos day lasts 7.65 earth hours, which yields about 300 extreme temperature cycles for the total mission time of three earth months. These cycles and the wide span of surface temperature between day and night are the main design drivers for the rover. This paper gives a detailed view on the development of the MMX rover locomotion subsystem.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: Recognising the importance of astrobiology in Mars exploration, progress is highlighted in the area of autonomous biosignature detection capabilities trialed on Earth, and the objectives and challenges in relation to future missions to Mars are discussed.
Abstract: Autonomous mission planning for unmanned aerial vehicles (UAVs) aims to leverage the capabilities of UAVs equipped with on-board sensors to accomplish a wide range of applications, including planetary exploration where greater science yields can be achieved at lower costs over shorter time periods. A significant body of research has already been performed with the aim of improving the autonomy of UAV missions, particularly in the areas of navigation and target identification. In this work, we review current approaches to drone navigation and exploration for planetary missions, with a focus on Mars and the main autonomy levels/techniques employed to achieve these levels. Recognising the importance of astrobiology in Mars exploration, we highlight progress in the area of autonomous biosignature detection capabilities trialed on Earth, and discuss the objectives and challenges in relation to future missions to Mars. Finally, we indicate currently available software tools and future work to improve autonomous mission planning capabilities.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: Detailed analysis of each subsystem of sphereX is presented and also detailed dynamics and control simulations of SphereX for ballistic hopping and rolling mobility are presented.
Abstract: High-resolution orbital imagery from the LROC reveals evidence of subsurface voids and mare-pits on the lunar surface. Similar discoveries have been made with the HiRISE camera onboard the MRO observing the Martian surface. These accessible voids could be used for a future human base because they offer a natural radiation and micrometeorite shield and offer constant habitable temperatures. Exploration of these extreme and rugged environments remains out of reach from current planetary rovers and landers. A credible solution is to develop an architecture that permits taking high exploratory risks that translates into high reward science. Rapid advancement in electronics, sensors, actuators, and power have resulted in ever-shrinking devices and instruments that can be housed in small platforms. We propose to use a small, low-cost, modular spherical robot called SphereX that is designed to hop and roll short distances. Each robot is of several kilograms in mass and several liters in volume. Each SphereX will consist of space-qualified electronics like command & data handling board, power board for power management and s-band radio transceiver for communication. Power is provided using lithium-ion primary batteries or a PEM fuel cell power supply. Communication is established through multi-hop communication link to relay data from inside the caves to a lander outside on the planetary surface. Since the temperature inside underground lunar pits is expected at -25°C, thermal management for the space-grade electronics is minimal as they can operate up to -40°C, however thermal management for the battery pack and the propellants will be done through active and passive elements. Moreover, SphereX requires use of a propulsion system and Attitude Determination and Control System (ADCS) to perform controlled ballistic hops. Hopping on very-low gravity environments is more time-efficient than rolling due to the reduced traction. In this paper, we present detailed analysis of each subsystem of SphereX and also detailed dynamics and control simulations of SphereX for ballistic hopping and rolling mobility. For ballistic hopping control, the robot has two modes: soft landing mode for traversing long distances and entering the pit through its collapsed entrance, and a fuel-efficient hard landing mode for traversing short distances. We will then present experimental results for mapping unknown cave-like environments which is done using a quadcopter for simulating low-gravity (e.g. Moon, Mars) environments and testing the control algorithms. The quadcopter mimics the dynamics of SphereX and also carries a 3D LiDAR for mapping and navigation. 3D point cloud data collected by the LiDAR is used for performing SLAM and path planning in unknown and GPS-denied environments much like the pits, caves and lava tubes on the Moon and Mars.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: This work proposes leveraging distributed ledger technologies (i.e. blockchains) to develop a secure, decentralized reputation system for satellite relay networks that informs a reputation-aware routing protocol and reduces the average data latency across the network.
Abstract: Currently, space communications networks are attempting to move away from large geostationary (GEO) satellites towards large constellations of small satellites. This trend is observed both in government and commercial communications satellites. By relaying data across multiple constellations/networks, we may be able to reduce end-to-end latencies and reduce burden (mass, power, cost) for all users. However, this is only possible if networks across constellations can establish inter-satellite authentication and trust. The key to this trust is based on demonstrated ability of the relay satellites to meet performance requirements, i.e. “reputation.” In this work, we propose leveraging distributed ledger technologies (i.e. blockchains) to develop a secure, decentralized reputation system for satellite relay networks. This informs a reputation-aware routing protocol and reduces the average data latency across the network. In this paper, we discuss designing the blockchain-based reputation system and routing protocol. We then analyze the resultant network performance with respect to average latency, computational complexity, and storage considerations for a variety of use cases.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: Moon Diver as discussed by the authors is a mission to land and deploy an extreme-terrain, tethered rover for the exploration of Tran-quillitatis Pit, a large vertical cave entrance into the subsurface of Earth's Moon.
Abstract: Moon Diver is a proposed mission to land and deploy an extreme-terrain, tethered rover for the exploration of Tran-quillitatis Pit, a large vertical cave entrance into the subsurface of Earth's Moon. By leveraging a supportive tether, the Axel rover, developed by NASA's Jet Propulsion Laboratory, would perform a controlled descent into the pit and deploy instruments along the pit wall. The purpose of this mission concept is to study a volcanic secondary crust as a function of depth in order to determine formation processes and chemical makeup. The lifeline of the mission would be the tether, which provides power from, and communication to the top-side lander. Critically, the tether also serves as mechanical support between the suspended rover and the lander, which acts as an anchor. While space tethers have been deployed both in orbit and terrestrially, the use of the proposed tether is unlike any known in the literature; the tether must come into contact with the terrain while under load. With respect to the environment, the tether must also survive abrasion from glassy regolith and volcanic rocks, bending around sharp edges, thermal extremes, and exposure to full spectrum ultra-violet (UV) radiation, all while reliably transferring up to 100 W of power and 1 Mbps of data. Furthermore, since the Axel rover pays out tether from an internal spool, the tether's diameter must be minimized to increase spool capacity, allowing for up to a 300-m traverse while also meeting static and dynamic strength requirements. This paper covers several phases of the tether's initial development, including i) a trade study of structure and materials with consideration for space heritage, ii) selected design justification, and iii) results from tests on prototype tethers looking into mechanical, electrical, and environmental properties, including exposure to rock-regolith abrasion, load profiles at temperature, and degradation due to UV exposure while exposed to vacuum. Finally, we provide insights and lessons learned from lab and field tests, which inform our continued effort to design a tether capable of surviving rugged, lunar conditions.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: The Adaptable Human-Machine Interface was developed for hardware-in-the-loop laboratory experiments with a Parrot A.R. Drone 2.0 quadcopter as test case and the graphical display itself was developed in the Unity3D game engine.
Abstract: Current plans for the exploration of Moon and Mars envision the use of telerobotic systems controlled from orbiting laboratories. The advantage of telerobotics is that it combines the resilience, endurance and precision of robots with the inherent flexibility, anticipation and decision making capabilities of humans. The primary disadvantage of telerobotics is the communication time delay in the human-robot control loop. The delay can lead to a loss of situation awareness, an increase in operator work load, and an overall decrease in effectiveness and efficiency of the human-robot system. Most of the effects of the delay can be mitigated by the use of predictive displays, presenting the operator with a simulated system state. This paper presents current work on such a predictive display designed to support an operator in remote flight and landing of space robots and unmanned aerial vehicles. The Adaptable Human-Machine Interface was developed for hardware-in-the-loop laboratory experiments with a Parrot A.R. Drone 2.0 quadcopter as test case. Based on live video from two on-board cameras, attitude and velocity telemetry, and control inceptor deflection, the interface calculates a predicted flight path and attitude and presents it in a “tunnel in the sky” display. The graphical display itself was developed in the Unity3D game engine. The paper describes the implementation of the interface between Unity3D and the A.R. Drone, the dynamic model of the quadcopter, and the prediction algorithm. The paper also discusses the results of flight tests involving a number of test subjects and projects the path forward in the development of this technology.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: An overview of the ROS-based simulator used for testing the M2020 ENav algorithms, which simulates the physics of the rover motion, the point cloud perceived by the rover's stereo vision system, and the new thinking-while-driving (TWD) navigation logic which directs the rover to drive autonomously to user-specified waypoints.
Abstract: In order to achieve the ambitious objectives of the Mars 2020 (M2020) mission, in particular the ability to autonomously traverse more challenging terrains more efficiently, new surface mobility software was developed for Enhanced Navigation (ENav). That decision was made early in the project, before most of the new surface flight software (FSW) existed, which created a need for a separate framework where the new navigation algorithms could be quickly prototyped and tested, before more realistic FSW-based testbeds became available. The JPL robotics team chose the Robot Operating System [1] (ROS) as the environment in which to test the new ENav algorithms. This made it possible to write the algorithms in the C language required by the FSW, so they could be directly ported over to the flight module later on, while leveraging all the C++ libraries and tools provided by ROS for simulation and testing. The ENav algorithms were developed as a separate C library, and stubs were used to replace any FSW-specific code, such as Event Reporting (EVRs) and data products (DPs). A ROS simulator was developed to generate a rich set of varied 3D terrains representative of the candidate Mars landing sites and simulate the physics of the rover motion, the point cloud perceived by the rover's stereo vision system, and the new thinking-while-driving (TWD) navigation logic which directs the rover to drive autonomously to user-specified waypoints. To simulate the rover motion and perception, a ROS node was developed that uses a software library called HyperDrive Sim (HDSim), which is a wrapper for the Rover Sequencing and Visualization Program [2] (RSVP). That library provides rover-terrain settling, realistic slip modelling, and camera rendering capability based on the rover's NavCam machine vision models. To simulate the navigation logic, a ROS node was created that initializes and runs the ENav algorithms in a way that mimics the FSW execution, while also providing the capability to load and replay data products, including re-running the recorded inputs through the ENav algorithms for testing. An engineering Graphical User Interface (GUI) was also developed to visualize various elements, such as the rover pose during the drive, the simulated and perceived terrain, the selected local and global paths to the goal, the evaluated candidate paths and the reasons why they were rejected, the keep-in and keep-out zones (KIOZs), etc. Finally, an advanced Monte Carlo (MC) framework that can run many simulations in parallel on the Cloud and automatically generate reports that capture the key ENav performance metrics was developed to evaluate the system in a statistically-meaningful way. This paper provides an overview of the ROS-based simulator used for testing the M2020 ENav algorithms.

Proceedings ArticleDOI
01 Jul 2020
TL;DR: This paper presents a reference architecture that can be used to abstractly model in situ applications of this new space landscape and demonstrates how to analyse the attack surface using attack trees.
Abstract: The space environment is currently undergoing a substantial change and many new entrants to the market are deploying devices, satellites and systems in space; this evolution has been termed as NewSpace. The change is complicated by technological developments such as deploying machine learning based autonomous space systems and the Internet of Space Things (IoST). In the IoST, space systems will rely on satellite-to-x communication and interactions with wider aspects of the ground segment to a greater degree than existing systems. Such developments will inevitably lead to a change in the cyber security threat landscape of space systems. Inevitably, there will be a greater number of attack vectors for adversaries to exploit, and previously infeasible threats can be realised, and thus require mitigation. In this paper, we present a reference architecture (RA) that can be used to abstractly model in situ applications of this new space landscape. The RA specifies high-level system components and their interactions. By instantiating the RA for two scenarios we demonstrate how to analyse the attack surface using attack trees.

Proceedings ArticleDOI
07 Mar 2020
TL;DR: The Shapeshifter is a collection of simple and affordable robotic units, called Cobots, comparable to personal palm-size quadcopters that allow multi-domain and redundant mobility on Saturn's moon Titan, and potentially other bodies with atmospheres.
Abstract: In this paper we present a mission architecture and a robotic platform, the Shapeshifter, that allow multi-domain and redundant mobility on Saturn's moon Titan, and potentially other bodies with atmospheres. The Shapeshifter is a collection of simple and affordable robotic units, called Cobots, comparable to personal palm-size quadcopters. By attaching and detaching with each other, multiple Cobots can shape-shift into novel structures, capable of (a) rolling on the surface, to increase the traverse range, (b) flying in a flight array formation, and (c) swimming on or under liquid. A ground station complements the robotic platform, hosting science instrumentation and providing power to recharge the batteries of the Cobots. In the first part of this paper we experimentally show the flying, docking and rolling capabilities of a Shapeshifter constituted by two Cobots, presenting ad-hoc control algorithms. We additionally evaluate the energy-efficiency of the rolling-based mobility strategy by deriving an analytic model of the power consumption and by integrating it in a high-fidelity simulation environment. In the second part we tailor our mission architecture to the exploration of Titan. We show that the properties of the Shapeshifter allow the exploration of the possible cryovolcano Sotra Patera, Titan's Mare and canyons.

Proceedings ArticleDOI
01 Mar 2020
TL;DR: Simulation of the visibility of GNSS satellites by a lunar vehicle in a Near Rectilinear Halo Orbit, and the preliminary results show that the lunar vehicle can “see” 5 − 13 satellites, and achieve a 3D positioning error of 200–300 meters based on reasonable ephemeris and pseudorange error assumptions.
Abstract: There are multiple Global Navigation Satellite Systems (GNSS's), comprising over 100 navigation satellites in the Earth's medium and high orbits. Most of these satellites have antennas that point nadir to earth, and transmit navigation signals so vehicles on Earth's surface and in its vicinity can perform trilateration and estimate its 3-dimenional (3D) positioning. The sidelobes of these antennas can occasionally point to the Moon. It is postulated that a lunar vehicle carrying a large enough receiving antenna can occasionally detects and receives four or more sidelobes of these weak GNSS signals, thus enabling the vehicle to perform 3D positioning using an onboard GNSS receiver. We propagate the orbits of the GNSS satellites from United States' Global Positioning Satellite (GPS) constellation, the Europe's Galileo constellation, and the Russia's GLONASS constellation, to a total of 81 satellites. We simulate the visibility of these satellites by a lunar vehicle in a Near Rectilinear Halo Orbit (NRHO), based on the assumption that the lunar vehicle is “in-view” of a GNSS satellite as long as it falls within the 40-degree beam width of the satellite. We also simulate the 3D positioning performance as a function of satellites' ephemeris errors and pseudo-range errors. The preliminary results show that the lunar vehicle can “see” 5 − 13 satellites, and achieve a 3D positioning error (one-sigma) of 200–300 meters based on reasonable ephemeris and pseudorange error assumptions. We also consider the case of using relative positioning to mitigate the GNSS satellites' ephemeris biases; that is, we assume a reference receiver with accurately known positioning that is close to the lunar vehicle and then compute the relative position of the lunar vehicle with respect to the reference.