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The paper summarizes efforts at JPL to develop an intelligent autonomous tracking and pointing system for space applications. A powerful 3D graphic software testbed has also been developed to simulate a likely scenario of autonomous tracking and pointing operations during a planetary flyby.
As missions in Low Earth Orbit (LEO) lengthen and extend to deep space, minimizing resupply needs becomes vital for sustaining crewed operations. Traditional life support systems depend on consumables resupplied from Earth, a method that is increasingly impractical for missions beyond LEO, such as lunar outposts or Mars transit. Long-duration missions require more efficient, autonomous systems that can recycle essential resources, particularly water and oxygen, to minimize the frequency and mass of resupply missions. The Environmental Control and Life Support System (ECLSS) is essential to such missions, with the International Space Station (ISS) serving as a testbed for advanced water recovery and partial oxygen recycling via physico-chemical methods. Yet, ECLSS and propulsion subsystems generally operate independently, despite overlapping requirements and potential areas for synergy. For instance, ECLSS byproducts, water, CO₂, and hydrogen, could be repurposed for propulsion, potentially reducing dedicated propellant mass and increasing overall system efficiency. One promising approach is to develop shared-resource architectures that integrate ECLSS with propulsion systems. This study examines the potential of such integration through the Sabatier CO₂ reduction process, focusing on water management as a key factor in system mass trade-offs. The Sabatier reaction produces water and methane from metabolic CO₂ and electrolytic hydrogen, partially closing the life support loop and providing methane, which could serve as a propellant. This integration could minimize waste, reduce resupply requirements, and enhance mission mass efficiency. A dynamic modeling framework will be used to simulate resource flows over long missions, capturing interactions between life support and propulsion. By comparing integrated versus separate system configurations, the study aims to quantify mass benefits and penalties, informing future habitat designs and trade studies for missions prioritizing autonomy and mass efficiency.
As missions in low Earth orbit (LEO) lengthen and extend to deep space, minimizing resupply needs becomes vital for sustaining crewed operations. Traditional life support systems depend on consumables resupplied from Earth, a method that is increasingly impractical for missions beyond LEO, such as lunar outposts or Mars transit. Long-duration missions require more efficient, autonomous systems that can recycle essential resources, particularly water and oxygen, to minimize the frequency and mass of resupply missions. The Environmental Control and Life Support System (ECLSS) is essential to such missions, with the International Space Station (ISS) serving as a testbed for advanced water recovery and partial oxygen recycling via physico-chemical methods. Yet, ECLSS and propulsion subsystems generally operate independently, despite overlapping requirements and potential areas for synergy. For instance, ECLSS byproducts, water, CO 2 , and hydrogen, could be repurposed for propulsion, potentially reducing dedicated propellant mass and increasing overall system efficiency. One promising approach is to develop shared-resource architectures that integrate ECLSS with propulsion systems. This study examines the potential of such integration through the Sabatier CO₂ reduction process, focusing on water management as a key factor in system mass trade-offs. The Sabatier reaction produces water and methane from metabolic CO 2 and electrolytic hydrogen, partially closing the life support loop and providing methane, which could serve as a propellant. This integration could minimize waste, reduce resupply requirements, and enhance mission mass efficiency. A dynamic modeling framework will be used to simulate resource flows over long missions, capturing interactions between life support and propulsion. By comparing integrated versus separate system configurations, the study aims to quantify mass benefits and penalties, informing future habitat designs and trade studies for missions prioritizing autonomy and mass efficiency.
An approach is presented supporting analysis, modeling, and test validation of operational flight instrumentation (OFI) that facilitates critical functions for the Space Launch System (SLS) main propulsion system (MPS). Certain types of OFI sensors were shown to exhibit highly nonlinear and non-gaussian noise characteristics during acceptance testing, motivating the development of advanced modeling and simulation (M&S) capability to support algorithm verification and flight certification. Hardware model and algorithm simulation fidelity was informed by a risk scoring metric; redesign of high-risk algorithms using test-validated sensor models significantly improved their expected performance as evaluated using Monte Carlo acceptance sampling methods. Autonomous functions include closed-loop ullage pressure regulation, pressurant leak detection, and fault isolation for automated safing and crew caution and warning (C&W).
Objectives for Phase II of NASA’s Artemis Program include establishment of lunar surface infrastructure to support a sustainable, long-term human presence on the Moon. Terrestrially, awareness of climate impacts from cement and concrete production has led to renewed interest in traditional building materials using earthen and pozzolanic binders with locally sourced aggregates [1, 2, 3]. In remote, austere,and resource-constrained environments, use of site-sourced materials is often an economic necessity in addition to being valuable for local autonomy and self-sufficiency. This study evaluates modifications to ASTM cement mortar testing methods, incorporating details from European standards for earthen plasters and lime-based mortars. Development of consistent, simplified methods for evaluating in-situ materials will be essential not only for meeting future climate goals and sustainable construction needs, but also for conducting autonomous robotic manipulation and evaluation of regolith construction materials.
The use and acceptance of new high-performance, parallel computing platforms will be impeded by the absence of an infrastructure capable of supporting orders-of-magnitude improvement in hierarchical storage and high-speed I/O (Input/Output). The distribution of these high-performance platforms and supporting infrastructures across a wide-area network further compounds this problem. We describe an architectural design and phased implementation plan for a distributed, Cooperative Storage Environment (CSE) to achieve the necessary performance, user transparency, site autonomy, communication, and security features needed to support the Accelerated Strategic Computing Initiative (ASCI). ASCI is a Department of Energy (DOE) program attempting to apply terascale platforms and Problem-Solving Environments (PSEs) toward real-world computational modeling and simulation problems. The ASCI mission must be carried out through a unified, multilaboratory effort, and will require highly secure, efficient access to vast amounts of data. The CSE provides a logically simple, geographically distributed, storage infrastructure of semi-autonomous cooperating sites to meet the strategic ASCI PSE goal of highperformance data storage and access at the user desktop.
A key enabling technology that leads to greater spacecraft autonomy is the capability to autonomously and optimally slew the spacecraft from and to different attitudes while operating under a number of celestial and dynamic constraints. The task of finding an attitude trajectory that meets all the constraints is a formidable one, in particular for orbiting or fly-by spacecraft where the constraints and initial and final conditions are of time-varying nature. This paper presents an approach for attitude path planning that makes full use of a priori constraint knowledge and is computationally tractable enough to be executed on-board a spacecraft. The approach is based on incorporating the constraints into a cost function and using a Genetic Algorithm to iteratively search for and optimize the solution. This results in a directed random search that explores a large part of the solution space while maintaining the knowledge of good solutions from iteration to iteration. A solution obtained this way may be used 'as is' or as an initial solution to initialize additional deterministic optimization algorithms. A number of example simulations are presented including the case examples of a generic Europa Orbiter spacecraft in cruise as well as in orbit around Europa. The search times are typically on the order of minutes, thus demonstrating the viability of the presented approach. The results are applicable to all future deep space missions where greater spacecraft autonomy is required. In addition, onboard autonomous attitude planning greatly facilitates navigation and science observation planning, benefiting thus all missions to planet Earth as well.
This presentation is a technical update for the NATO-STO HFM-247 working group. Our progress on four goals will be discussed. For Goal 1, a conceptual model of HAT is presented. HAT looks to make automation act as more of a teammate, by having it communicate with human operators in a more human, goal-directed, manner which provides transparency into the reasoning behind automated recommendations and actions. This, in turn, permits more trust in the automation when it is appropriate, and less when it is not, allowing a more targeted supervision of automated functions. For Goal 2, we wanted to test these concepts and principles. We present findings from a recent simulation and describe two in progress. Goal 3 was to develop pattern(s) of HAT solution(s). These were originally presented at HCII 2016 and are reviewed. Goal 4 is to develop a re-usable HAT software agent. This is an ongoing effort to be delivered October 2017.
To achieve NASA’s Artemis program mission objectives a high level of autonomy and ubiquitous autonomy throughout the systems that are being developed will be necessary. The autonomous systems of Artemis will require a distributed autonomy capability, with autonomous systems organized functionally in a hierarchical architecture, where systems at higher levels of the hierarchy have authority over systems at lower levels. The challenge of developing autonomy technologies and concepts of operations for Artemis has been undertaken by the NASA Gateway Working Group. This group has developed requirements, architectures, concepts of operations, and interface control documents, in the context of a hierarchical distributed architecture that includes the following: a Vehicle System Manager (VSM) that autonomously manages the entire Gateway; Module System Managers (MSMs) that autonomously manage each module; and System Managers (SMs) that autonomously manage systems within a module(i.e. ECLSS).A substantially high level of autonomy needs to be achieved by each element of the hierarchy (VSM, MSM, SM)to meet requirements for uncrewed operations; this includes conditions that will have minimal and/or delayed ground intervention (i.e. requirements for sustainability for months of operation without crew or ground support). To advance an implementation of this autonomy design (Gateway Autonomy Design –GAD), a collaboration was established between the Autonomous Systems Laboratory (ASL) at NASA Stennis Space Center and Lockheed Martin. The objectives of this partnership were the following: (1)to implement autonomy at the VSM, MSM, and SM levels;(2) to implement communications among a VSM, 2 MSMs, ORION (a visiting vehicle somewhat equivalent to a module) and 1 SM (a power system), and (3) test autonomous operations with representative use cases. A SM backed by a high-fidelity simulation was created to facilitate demonstrations of use cases that originated in a system of a module. Communication between the VSM and MSMs was implemented according to Concepts of Operations and Interface Control Documents (ICDs). Demonstrations were conducted to address nominal and off-nominal operations and multi-module interactions with VSM. Additionally, user interfaces were created to provide awareness about ongoing processes and results while enhancing the demonstration. Demonstrations included the following use cases: (1)Orion as visiting vehicle registers with VSM;(2) VSM reschedules a module’s timelines when another module’s MSM task fails; and (3) a module’s Power System Manager (PSM) standalone demonstration that included component failure diagnostics, tracing component failure to effected components, which in turn, reports failure information up to the VSM for acknowledgement and display. This paper will describe the detailed technology and autonomous systems developed, and the integrated multi-module demonstrations conducted. Also, challenges that must be met to fully implement the GAD defined by Gateway will be addressed.
Autonomous systems governed by a variety of adaptive and nondeterministic algorithms are being planned for inclusion into safety-critical environments, such as unmanned aircraft and space systems in both civilian and military applications. However, until autonomous systems are proven and perceived to be capable and resilient in the face of unanticipated conditions, humans will be reluctant or unable to delegate authority, remaining in control aided by machine-based information and decision support. Proving capability, or trustworthiness, is a necessary component of certification. Perceived capability is a component of trust. Trustworthiness is an attribute of a cyber-physical system that requires context-driven metrics to prove and certify. Trust is an attribute of the agents participating in the system and is gained over time and multiple interactions through trustworthy behavior and transparency. Historically, artificial intelligence and machine learning systems provide answers without explanation - without a rationale or insight into the machine “thinking”. In order to function as trusted teammates, machines must be able to explain their decisions and actions. This transparency is a product of both content and communication. NASA’s Autonomy Teaming & TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) project seeks to build a basis for certification of autonomous systems via establishing metrics for trustworthiness and trust in multi-agent team interactions, using AI (Artificial Intelligence) explainability and persistent modeling and simulation, in the context of mission planning and execution, with analyzable trajectories. Inspired by Massively Multiplayer Online Role Playing Games (MMORPG) and Serious Gaming, the proposed ATTRACTOR modeling and simulation environment is similar to online gaming environments in which player (aka agent) participants interact with each other, affect their environment, and expect the simulation to persist and change regardless of any individual agent’s active participation. This persistent simulation environment will accommodate individual agents, groups of self-organizing agents, and large-scale infrastructure behavior. The effects of the emerging adaptation and coevolution can be observed and measured to building a basis of measurable trustworthiness and trust, toward certification of safety-critical autonomous systems.
The MIT's Space Systems Laboratory developed the Synchronized Position Hold Engage and Reorient Experimental Satellites (SPHERES) as a risk-tolerant spaceborne facility to develop and mature control, estimation, and autonomy algorithms for distributed satellite systems for applications such as satellite formation flight. Tests performed study interferometric mission-type formation flight maneuvers in deep space. These tests consist of having the satellites trace a coordinated trajectory under tight control that would allow simulated apertures to constructively interfere observed light and measure the resulting increase in angular resolution. This paper focuses on formation initialization (establishment of a formation using limited field of view relative sensors), formation coordination (synchronization of the different satellite s motion) and fuel-balancing among the different satellites.
The NASA Next Space Technologies for Exploration Partnerships (NextSTEP) program is a public-private partnership model that seeks commercial development of deep space exploration capabilities to support human spaceflight missions around and beyond cislunar space. NASA first issued the Phase 1 NextSTEP Broad Agency Announcement to U.S. industries in 2014, which called for innovative cislunar habitation concepts that leveraged commercialization plans for low-Earth orbit. These habitats will be part of the Deep Space Gateway (DSG), the cislunar space station planned by NASA for construction in the 2020s. In 2016, Phase 2 of the NextSTEP program selected five commercial partners to develop ground prototypes. A team of NASA research engineers and subject matter experts (SMEs) have been tasked with developing the ground-test protocol that will serve as the primary means by which these Phase 2 prototypes will be evaluated. Since 2008, this core test team has successfully conducted multiple spaceflight analog mission evaluations utilizing a consistent set of operational tools, methods, and metrics to enable the iterative development, testing, analysis, and validation of evolving exploration architectures, operations concepts, and vehicle designs. The purpose of implementing a similar evaluation process for the Phase 2 Habitation Concepts is to consistently evaluate different commercial partner ground prototypes to provide data-driven, actionable recommendations for Phase 3. This paper describes the process by which the ground test protocol was developed and the objectives, methods, and metrics by which the NextSTEP Phase 2 Habitation Concepts will be rigorously and systematically evaluated. The protocol has been developed using both a top-down and bottom-up approach. Top-down development began with the Human Exploration and Operations Mission Directorate (HEOMD) exploration objectives and ISS Exploration Capability Study Team (IECST) candidate flight objectives. Strategic questions and associated rationales, derived from these candidate architectural objectives, provide the framework by which the ground-test protocol will address the DSG stack elements and configurations, systems and subsystems, and habitation, science, and EVA functions. From these strategic questions, high-level functional requirements for the DSG were drafted and associated ground-test objectives and analysis protocols were established. Bottom-up development incorporated objectives from NASA SMEs in autonomy, avionics and software, communication, environmental control and life support systems, exercise, extravehicular activity, exploration medical operations, guidance navigation and control, human factors and behavioral performance, human factors and habitability, logistics, Mission Control Center operations, power, radiation, robotics, safety and mission assurance, science, simulation, structures, thermal, trash management, and vehicle health. Top-down and bottom-up objectives were integrated to form overall functional requirements - ground-test objectives and analysis mapping. From this mapping, ground-test objectives were organized into those that will be evaluated through inspection, demonstration, analysis, subsystem standalone testing, and human-in-the-loop (HITL) testing. For the HITL tests, mission-like timelines, procedures, and flight rules have been developed to directly meet ground test objectives and evaluate specific functional requirements. Data collected from these assessments will be analyzed to determine the acceptability of habitation element configurations and the combinations of capabilities that will result in the best habitation platform to be recommended by the test team for Phase 3.
Mobility is a generic capability needed for Mars exploration. Requirements for mobility range from those to get observations of individual rocks all the way to getting high resolution observations of regional areas. Table 1 shows the required-range of mobility to achieve various tasks. The Pathfinder mission and field experiments simulating rover missions [1, 2, 3, 4, 5] provide guidance as to rover capabilities that can reasonably be expected in the next decade. Rover mobility can be accomplished in a variety of ways, the most common being wheels or tracks and legged-walkers. Wheeled vehicles can traverse over rocks smaller than 1/2 wheel diameter, and with path planning to avoid larger rocks, can traverse terrains comparable to those seen on Mars in the Viking and Pathfinder landing sites. Slopes of 45 deg can be easily negotiated by wheeled rovers. Walking vehicles can negotiate even more complex terrain but requires computation capability to select each leg placement. Extremely complex terrain was traversed by the Nomad II walker which descended into (and most of the way out of) an active volcanic caldera (Mount Spur, AK) in 1995, although a slope failure eventually resulted in broken legs. The traverse range of a rover is limited by its science objectives, performance capabilities, and operational lifetime. The speed of rover traverse is a relative minor factor. With a different communication system, and no stops for science experiments, Sojourner could probably have traveled a kilometer. But, achieving land speed records is not a major objective of a science mission. Achieving science objectives requires targeting particular objects and studying them in detail, and the associated operational requirements will likely limit rover traverse range significantly. Traversing from target to target requires relatively few command cycles provided the traverse is over a short enough distance that it can be adequately planned. An operational goal of 100 m traverse per command cycle, arriving at a predetermined target, seems achievable. Investigating science targets requiring manipulator or instrument placement and sample collection will likely take several command cycles per target. Mission simulations [6] have demonstrated that traverse dI stances of 100-300 m, with detailed investigation of 5-10 targets take 50-100 command cycles, not unlike the Pathfinder experience in spite of the use of larger, faster, more capable rovers. Significant advances in rover autonomy will be needed to improve this Situation and it is not clear how much improvement will be brought to flight programs in the next decade. Dust accumulation on solar panels degrades power over time and, without dust removal, rover operational lifetimes may be limited to 90 sols.
Future Mars Rotorcrafts require advanced navigation capabilities to enable all terrain access for science investigations with long distance flights that are executed fully autonomously. A critical component is the ability to safely land in hazardous terrain as part of a mission, or triggered by an emergency situation. In this paper, we present an advanced navigation system for continuous on-board terrain reconstruction for the purpose of hazard-free landing site detection for the autonomous navigation of a Mars Science Helicopter - a JPL research concept that investigates the feasibility of flying a multi-kilogram science payload at various Mars science locations, with flight ranges of multiple kilometers per flight. Our approach builds on a visionbased perception system that incorporates an on-board visualinertial state estimator augmented by a laser altimeter (range- VIO), and a structure-from-motion 3D reconstruction approach that uses a single, downward-looking camera to provide dense depth measurements while the vehicle is in motion. Depth measurements are accumulated in a local, robot-centric, multiresolution elevation map that is analyzed by a landing site detector to extract safe landing areas below the rotorcraft, based on a heuristic that includes slope, roughness and the presence of landing hazards. Detected landing sites are prioritized by an on-board autonomy engine that either selects suitable landing sites for immediate landing maneuvers, or can explore a terrain location as part of a mission in order to find a best landing site in a pre-planned area. We demonstrate and evaluate our approach on simulated data and data acquired with a surrogate unmanned aerial system (UAS) executing flights over relevant terrain.
Autonomous systems (AS) are crucial to realizing the vision of new, complex transportation modes, such as advanced air mobility (AAM) and urban air mobility (UAM). A chief barrier to induction of AS into aviation is insufficient understanding of AS reliability in time-critical and safety-critical environments—an obstacle to certification. ATTRACTOR is aimed at building a basis for certification of classes of autonomous cyber-physical-human systems (CPHS) via establishing metrics and models of trustworthiness and trust in multi-agent team interactions, analyzable trajectories, explainability of computational algorithms (explainable artificial intelligence, or XAI), and persistent modeling and simulation, in the context of missions planning and operation. By “building a basis for certification,” we mean acquiring an understanding of when a system is trustworthy and developing computable means to estimate trustworthiness and trust in order to eventually inform functional requirements that contribute to certification. The outcomes are applicable not just to aviation but to all domains that rely on autonomous systems.
The success of JPL's AutoNav system at comet Tempel-1 on July 4, 2005, demonstrated the power of autonomous navigation technology for the Deep Impact Mission. This software is being planned for use as the onboard navigation, tracking and rendezvous system for a Mars Sample Return Mission technology demonstration, and several mission proposals are evaluating its use for rendezvous with, and landing on asteroids. Before this however, extensive re-engineering of AutoNav will take place. This paper describes the AutoNav systems-engineering effort in several areas: extending the capabilities, improving operability, utilizing new hardware elements, and demonstrating the new possibilities of AutoNav in simulations.
This article presents a framework for searching, detecting, and tracking an object of interest with a small unmanned aerial vehicle (sUAV). The vehicle is given an area to search for an object of interest. Once the object is detected, the sUAV follows the target while maintaining a fixed distance and centered on its image plane. This paper describes an architecture for integrating autonomy capabilities for search and track for sUAVs. The system has been implemented in the Robot Operating System (ROS) framework using the Parrot ARDrone platform. In this paper we present our technical approach, the system architecture and demonstrate the principles of the approach in a simulation environment and indoor flight tests.
We present an multi-agent model-based autonomy architecture with monitoring, planning, diagnosis, and execution elements. We discuss an internal spacecraft free-flying robot prototype controlled by an implementation of this architecture and a ground test facility used for development. In addition, we discuss a simplified environment control life support system for the spacecraft domain also controlled by an implementation of this architecture. We discuss adjustable autonomy and how it applies to this architecture. We describe an interface that provides the user situation awareness of both autonomous systems and enables the user to dynamically edit the plans prior to and during execution as well as control these agents at various levels of autonomy. This interface also permits the agents to query the user or request the user to perform tasks to help achieve the commanded goals. We conclude by describing a scenario where these two agents and a human interact to cooperatively detect, diagnose and recover from a simulated spacecraft fault.