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Robotic lighter-than-air vehicles, or aerobots, provide strategic platform for the exploration of planets and moons with an atmosphere, such as Venus, Mars, Titan and the gas giants. In this paper, we discuss steps towards the development of an autonomy architecture, and concentrate on the autonomous fight control subsystem.
Robotic lighter-than-air vehicles, or aerobots, provide a strategic platform for the exploration of planets and moons with an atmosphere, such as Venus, Mars, Titan and the gas giants.
The current transformation from a NASA of loosely coupled enterprises to 'one NASA' which embodies cross-enterprises Agency Missions and an Integrated Space Plan, has created an important need for an overall integrated Agency wide approach to systems analysis.
This paper describes the design and component testing of an aerobot that would be capable of global in situ exploration of Saturn's moon, Titan, over a 6 to 12 month mission lifetime. The proposed aerobot is a propeller-driven, buoyant vehicle that resembles terrestrial airships. However, the extremely cold Titan environment requires the use of cryogenic materials of construction and careful thermal design for protection of temperature-sensitive payload elements. Multiple candidate balloon materials have been identified based on extensive laboratory testing at 77 K. The most promising materials to date are laminates comprised of polyester fabrics and/or films with areal densities in the range of 40-100 g/m2. The aerobot hull is a streamlined ellipsoid 14 meters in length with a maximum diameter of 3 meters. The enclosed volume of 60 m3 is sufficient to float a mass of 234 kg at a maximum altitude of 8 km at Titan. Forward and aft ballonets are located inside the hull to enable the aerobot to descend to the surface while preserving a fully inflated streamlined shape. Altitude changes are effected primarily through thrust vectoring of the twin main propellers, with pressure modulated buoyancy change via the ballonets available as a slower backup option. A total of 100 W of electrical power is provided to the vehicle by a radioisotope power supply. Up to half of this power is available to the propulsion system to generate a top flight speed in the range of 1-2 m/s. This speed is expected to be greater than the near surface winds at Titan, enabling the aerobot to fly to and hover over targets of interest. A preliminary science payload has been devised for the aerobot to give it the capability for aerial imaging of the surface, atmospheric observations and sampling, and surface sample acquisition and analysis. Targeting, hovering, surface sample acquisition and vehicle health monitoring and automatic safing actions will all require significant on-board autonomy due to the over two hour round trip light time between Titan and Earth. An autonomy architecture and a core set of perception, reasoning and control technologies is under development using a free-flying airship testbed of approximately the same size as the proposed Titan aerobot. Data volume from the Titan science mission is expected to be on the order of 100-300 Mbit per day transmitted either direct to Earth through an 0.8 m high gain antenna or via an orbiter relay using an omni-directional antenna on the aerobot.
This paper describes an approach for qualifying optimal technology portfolios obtained with a multi-attribute decision support system. The goal is twofold: to gauge the degree of confidence in the optimal solution and to provide the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy non-technical constraints.
This paper describes the design and component testing of an aerobot that would be capable of global in situ exploration of Saturn's moon, Titan, over a 6 to 12 month mission lifetime. The proposed aerobot is a propeller-driven, buoyant vehicle that resembles terrestrial airships. However, the extremely cold Titan environment requires the use of cryogenic materials of construction and careful thermal design for protection of temperature-sensitive payload elements. Multiple candidate balloon materials have been identified based on extensive laboratory testing at 77 K.
In this paper, a systems engineering model is presented that identifies the technologies that proide the most significant impact for a given mission.
This paper presents global path planning algorithms for the Titan aerobot based on user defined waypoints in 2D and 3D space. The algorithms were implemented using information obtained through a planner user interface. The trajectory planning algorithms were designed to accurately represent the aerobot's characteristics, such as minimum turning radius. Additionally, trajectory planning techniques were implemented to allow for surveying of a planar area based solely on camera fields of view, airship altitude, and the location of the planar area's perimeter. The developed paths allow for planar navigation and three-dimensional path planning. These calculated trajectories are optimized to produce the shortest possible path while still remaining within realistic bounds of airship dynamics.
There is an important need for a consistent analytical foundation supporting the selection and monitoring of R&D tasks that support new system concepts that enable future NASA missions. This capability should be applicable at various degrees of abstraction, depending upon whether one is interested in formulation, development, or operations. It should also be applicable to a single project, a program comprised of a group of projects, an enterprise typically including multiple programs, and the overall agency itself. Emphasis here is on technology selection and new initiatives, but the same approach can be generalized to other applications, dealing, for example, with new system architectures, risk reduction, and task allocation among humans and machines. The purpose of this paper is to describe one such approach, which is in its early stages of implementation within NASA programs, and to discuss several illustrative examples.
This slide presentation reviews a process of postoptimally analysing the selection of technology portfolios. The rationale for the analysis stems from the need for consistent, transparent and auditable decision making processes and tools. The methodology is used to assure that project investments are selected through an optimization of net mission value. The main intent of the analysis is to gauge the degree of confidence in the optimal solution and to provide the decision maker with an array of viable selection alternatives which take into account input uncertainties and possibly satisfy non-technical constraints. A few examples of the analysis are reviewed. The goal of the postoptimality study is to enhance and improve the decision-making process by providing additional qualifications and substitutes to the optimal solution.
An architecture for autonomous operation of an aerobot (i.e., a robotic blimp) to be used in scientific exploration of planets and moons in the Solar system with an atmosphere (such as Titan and Venus) is undergoing development. This architecture is also applicable to autonomous airships that could be flown in the terrestrial atmosphere for scientific exploration, military reconnaissance and surveillance, and as radio-communication relay stations in disaster areas. The architecture was conceived to satisfy requirements to perform the following functions: a) Vehicle safing, that is, ensuring the integrity of the aerobot during its entire mission, including during extended communication blackouts. b) Accurate and robust autonomous flight control during operation in diverse modes, including launch, deployment of scientific instruments, long traverses, hovering or station-keeping, and maneuvers for touch-and-go surface sampling. c) Mapping and self-localization in the absence of a global positioning system. d) Advanced recognition of hazards and targets in conjunction with tracking of, and visual servoing toward, targets, all to enable the aerobot to detect and avoid atmospheric and topographic hazards and to identify, home in on, and hover over predefined terrain features or other targets of scientific interest. The architecture is an integrated combination of systems for accurate and robust vehicle and flight trajectory control; estimation of the state of the aerobot; perception-based detection and avoidance of hazards; monitoring of the integrity and functionality ("health") of the aerobot; reflexive safing actions; multi-modal localization and mapping; autonomous planning and execution of scientific observations; and long-range planning and monitoring of the mission of the aerobot. The prototype JPL aerobot (see figure) has been tested extensively in various areas in the California Mojave desert.
In order to explore Titan, a moon of Saturn, airships must be able to traverse the atmosphere autonomously. To achieve this, an accurate model and accurate control of the vehicle must be developed so that it is understood how the airship will react to specific sets of control inputs. This paper explains how longitudinal aircraft stability derivatives can be used with airship parameters to create a linear model of the airship solely by combining geometric and aerodynamic airship data. This method does not require system identification of the vehicle. All of the required data can be derived from computational fluid dynamics and wind tunnel testing. This alternate method of developing dynamic airship models will reduce time and cost. Results are compared to other stable airship dynamic models to validate the methods. Future work will address a lateral airship model using the same methods.
Algorithms for planning flight paths of autonomous aerobots (robotic blimps) to be deployed in scientific exploration of remote planets are undergoing development. These algorithms are also adaptable to terrestrial applications involving robotic submarines as well as aerobots and other autonomous aircraft used to acquire scientific data or to perform surveying or monitoring functions.
Current analysis of data streamed back to Earth by the Cassini spacecraft features Titan as one of the most exciting places in the solar system. NASA centers and universities around the US, as well as the European Space Agency, are studying the possibility of sending, as part of the next mission to this giant moon of Saturn, a hot-air balloon (Montgolfier-type) for further and more in-depth exploration. The basic idea would be to design a reliable, semi-autonomous, and yet cheap Montgolfier capable of using continuous flow of waste heat from a power source to lift the balloon and sustain its altitude in the Titan environment. In this paper we study the problem of locally navigating a hot-air balloon in the nitrogen-based Titan atmosphere. The basic idea is to define a strategy (i.e. design of a suitable guidance system) that allows autonomous and semi-autonomous navigation of the balloon using the available (and partial) knowledge of the wind structure blowing on the saturnian satellite surface. Starting from first principles we determined the appropriate thermal and dynamical models describing (a) the vertical dynamics of the balloon and (b) the dynamics of the balloon moving on a vertical plane (2-D motion). Next, various non-linear fuzzy-based control strategies have been evaluated, analyzed and implemented in MATLAB to numerically simulate the capability of the system to simultaneously maintain altitude, as well as a scientifically desirable trajectory. We also looked at the ability of the balloon to perform station keeping. The results of the simulation are encouraging and show the effectiveness of such a system to cheaply and effectively perform semiautonomous exploration of Titan.
Strategic Assessment of Risk and Technology (START) is a user-friendly computer program that assists human managers in making decisions regarding research-and-development investment portfolios in the presence of uncertainties and of non-technological constraints that include budgetary and time limits, restrictions related to infrastructure, and programmatic and institutional priorities. START facilitates quantitative analysis of technologies, capabilities, missions, scenarios and programs, and thereby enables the selection and scheduling of value-optimal development efforts. START incorporates features that, variously, perform or support a unique combination of functions, most of which are not systematically performed or supported by prior decision- support software. These functions include the following: Optimal portfolio selection using an expected-utility-based assessment of capabilities and technologies; Temporal investment recommendations; Distinctions between enhancing and enabling capabilities; Analysis of partial funding for enhancing capabilities; and Sensitivity and uncertainty analysis. START can run on almost any computing hardware, within Linux and related operating systems that include Mac OS X versions 10.3 and later, and can run in Windows under the Cygwin environment. START can be distributed in binary code form. START calls, as external libraries, several open-source software packages. Output is in Excel (.xls) file format.
A document describes a graph-based path-planning algorithm for balloons with vertical control authority and little or no horizontal control authority. The balloons are designed to explore celestial bodies with atmospheres, such as Titan, a moon of Saturn. The algorithm discussed enables the balloon to achieve horizontal motion using the local horizontal winds. The approach is novel because it enables the balloons to use arbitrary wind field models. This is in contrast to prior approaches that used highly simplified wind field models, such as linear, or binary, winds. This new approach works by discretizing the space in which the balloon operates, and representing the possible states of the balloon as a graph whose arcs represent the time taken to move from one node to another. The approach works with arbitrary wind fields, by looking up the wind strength and direction at every node in the graph from an arbitrary wind model. Having generated the graph, search techniques such as Dijkstra s algorithm are then used to find the set of vertical actuation commands that takes the balloon from the start to the goal in minimum time. In addition, the set of reachable locations on the moon or planet can be determined.
A parameterized linear mathematical model of the longitudinal dynamics of an airship is undergoing development. This model is intended to be used in designing control systems for future airships that would operate in the atmospheres of Earth and remote planets. Heretofore, the development of linearized models of the longitudinal dynamics of airships has been costly in that it has been necessary to perform extensive flight testing and to use system-identification techniques to construct models that fit the flight-test data. The present model is a generic one that can be relatively easily specialized to approximate the dynamics of specific airships at specific operating points, without need for further system identification, and with significantly less flight testing. The approach taken in the present development is to merge the linearized dynamical equations of an airship with techniques for estimation of aircraft stability derivatives, and to thereby make it possible to construct a linearized dynamical model of the longitudinal dynamics of a specific airship from geometric and aerodynamic data pertaining to that airship. (It is also planned to develop a model of the lateral dynamics by use of the same methods.) All of the aerodynamic data needed to construct the model of a specific airship can be obtained from wind-tunnel testing and computational fluid dynamics
We are developing onboard planning and execution technologies to provide robust and opportunistic mission operations for a potential Titan aerobot. Aerobot have the potential for collecting a vast amount of high priority science data. However, to be effective, an aerobot must address several challenges including communication constraints, extended periods without contact with Earth, uncertain and changing environmental conditions, maneuverability constraints and potentially short-lived science opportunities. We are developing the AerOASIS system to develop and test technology to support autonomous science operations for a potential Titan Aerobot. The planning and execution component of AerOASIS is able to generate mission operations plans that achieve science and engineering objectives while respecting mission and resource constraints as well as adapting the plan to respond to new science opportunities. Our technology leverages prior work on the OASIS system for autonomous rover exploration. In this paper we describe how the OASIS planning component was adapted to address the unique challenges of a Titan Aerobot and we describe a field demonstration of the system with the JPL prototype aerobot.