SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
An advanced design and implementation of a Control Architecture for Long Range Autonomous Planetary Rovers is presented using a hierarchical top-down task decomposition, and the common structure of each design is presented based on feedback control theory.
The principal accomplishments of the 1991 Nasa Planetary Rover Program are described. The work to date has focused on development of unmanned science rover technology within the context of high mobility wheeled vehicles at the JPL and an innovative legged locomotion concept at Carnegie Mellon University. Attention is given to mission operations research including simulation environment, mission scenario simulation experiments, and the rover system executive software that will reside onboard a rover in future planetary surface missions.
An advanced design and implementation of a Control Architecture for Long Range Autonomous Planetary Rovers is presented using a hierarchical top-down task decomposition, and the common structure of each design is presented based on feedback control theory. Graphical programming is presented as a common intuitive language for the design when a large design team is composed of managers, architecture designers, engineers, programmers, and maintenance personnel. The whole design of the control architecture consists in the classic control concepts of cyclic data processing and event-driven reaction to achieve all the reasoning and behaviors needed. For this purpose, a commercial graphical tool is presented that includes the mentioned control capabilities. Messages queues are used for inter-communication among control functions, allowing Artificial Intelligence (AI) reasoning techniques based on queue manipulation. Experimental results show a highly autonomous control system running in real time on top the JPL micro-rover Rocky 7 controlling simultaneously several robotic devices. This paper validates the sinergy between Artificial Intelligence and classic control concepts in having in advanced Control Architecture for Long Range Autonomous Planetary Rovers.
Automated planning and Scheduling, including automated path planning, has been integrated with an Internet-based distributed operations system for planetary rover operations. The resulting prototype system enables faster generation of valid rover command sequences by a distributed planetary rover operations team. The Web Interface for Telescience (WITS) provides Internet-based distributed collaboration, the Automated Scheduling and Planning Environment (ASPEN) provides automated planning and scheduling, and an automated path planner provided path planning. The system was demonstrated on the Rocky 7 research rover at JPL.
A Planetary Rover will have to be able to navigate through its local environment autonomously, due to communication delays. This implies that the vehicle must be able to sense its environment, plan a course through that environment, and react appropriately to unexpected situations as they appear. All this must be done while guiding the vehicle toward the goals that have been given to it from its operators on the earth. This paper describes research at the Jet Propulsion Laboratory which concentrates on the sensing, perception, planning and execution monitoring that must be carried out by the rover to ensure that a safe and efficient path is found by the rover, and that that path is performed correctly.
This video presentation explains the Planetary Rover Program and shows testing in the Arroyo near JPL.
Beginning next century, several schemes for sending a planetary rover to the moon or Mars are being planned. As part of the development program, autonomous navigation technology is being studied to allow the rover the ability to move autonomously over a long range of unknown planetary surface. In the previous study, we ran the autonomous navigation experiment on an outdoor test terrain by using a rover test-bed that was controlled by a conventional sense-plan-act method. In some cases during the experiment, a problem occurred with the rover moving into untraversable areas. To improve this situation, a new control technique has been developed that gives the rover the ability of reacting to the outputs of the proximity sensors, a reaction behavior if you will. We have developed a new rover test-bed system on which an autonomous navigation experiment was performed using the newly developed control technique. In this outdoor experiment, the new control technique effectively produced the control command for the rover to avoid obstacles and be guided to the goal point safely.
In planning for future exploration missions, architecture and study teams have made numerous assumptions about how crew can be telepresent on a planetary surface by remotely operating surface robots from space (i.e. from a flight vehicle or deep space habitat). These assumptions include estimates of technology maturity, existing technology gaps, and operational risks. These assumptions, however, have not been grounded by experimental data. Moreover, to date, no crew-controlled surface telerobot has been fully tested in a high-fidelity manner. To address these issues, we developed the "Surface Telerobotics" tests to do three things: 1) Demonstrate interactive crew control of a mobile surface telerobot in the presence of short communications delay. 2) Characterize a concept of operations for a single astronaut remotely operating a planetary rover with limited support from ground control. 3) Characterize system utilization and operator work-load for a single astronaut remotely operating a planetary rover with limited support from ground control.
During Summer 2013, we conducted a series of tests to examine how astronauts in the In- ternational Space Station (ISS) can remotely operate a planetary rover. The tests simulated portions of a proposed mission, in which an astronaut in lunar orbit remotely operates a planetary rover to deploy a radio telescope on the lunar farside. In this paper, we present the design, implementation, and preliminary test results.
A spectrum of concepts for planetary rovers and rover missions, is covered. Rovers studied range from tiny micro rovers to large and highly automated vehicles capable of traveling hundreds of kilometers and performing complex tasks. Rover concepts are addressed both for the Moon and Mars, including a Lunar/Mars common rover capable of supporting either program with relatively small modifications. Mission requirements considered include both Science and Human Exploration. Studies include a range of autonomy in rovers, from interactive teleoperated systems to those requiring and onboard System Executive making very high level decisions. Both high and low technology rover options are addressed. Subsystems are described for a representative selection of these rovers, including: Mobility, Sample Acquisition, Science, Vehicle Control, Thermal Control, Local Navigation, Computation and Communications. System descriptions of rover concepts include diagrams, technology levels, system characteristics, and performance measurement in terms of distance covered, samples collected, and area surveyed for specific representative missions. Rover development schedules and costs are addressed for Lunar and Mars exploration initiatives.
When planning planetary rover missions it is useful to develop intuition and skills driving in, quite literally, alien environments before incurring the cost of reaching said locales. Simulators make it possible to operate in environments that have the physical characteristics of target locations without the expense and overhead of extensive physical tests. To that end, NASA Ames and Open Robotics collaborated on a Lunar rover driving simulator based on the open source Gazebo simulation platform and leveraging ROS (Robotic Operating System) components. The simulator was integrated with research and mission software for rover driving, system monitoring, and science instrument simulation to constitute an end-to-end Lunar mission simulation capability. Although we expect our simulator to be applicable to arbitrary Lunar regions, we designed to a reference mission of prospecting in polar regions. The harsh lighting and low illumination angles at the Lunar poles combine with the unique reflectance properties of Lunar regolith to present a challenging visual environment for both human and computer perception. Our simulator placed an emphasis on high fidelity visual simulation in order to produce synthetic imagery suitable for evaluating human rover drivers with navigation tasks, as well as providing test data for computer vision software development.In this paper, we describe the software used to construct the simulated Lunar environment and the components of the driving simulation. Our synthetic terrain generation software artificially increases the resolution of Lunar digital elevation maps by fractal synthesis and inserts craters and rocks based on Lunar size-frequency distribution models. We describe the necessary enhancements to import large scale, high resolution terrains into Gazebo, as well as our approach to modeling the visual environment of the Lunar surface. An overview of the mission software system is provided, along with how ROS was used to emulate flight software components that had not been developed yet. Finally, we discuss the effect of using the high-fidelity synthetic Lunar images for visual odometry. We also characterize the wheel slip model, and find some inconsistencies in the produced wheel slip behaviour.
It is not yet clear of what type, and how much, intelligence is needed for a planetary rover to function semi-autonomously on a planetary surface. Current designs assume an advanced AI system that maintains a detailed map of its journeys and the surroundings, and that carefully calculates and tests every move in advance. To achieve these abilities, and because of the limitations of space-qualified electronics, the supporting rover is quite sizable, massing a large fraction of a ton, and requiring technology advances in everything from power to ground operations. An alternative approach is to use a behavior driven control scheme. Recent research has shown that many complex tasks may be achieved by programming a robot with a set of behaviors and activation or deactivating a subset of those behaviors as required by the specific situation in which the robot finds itself. Behavior control requires much less computation than is required by tradition AI planning techniques. The reduced computation requirements allows the entire rover to be scaled down as appropriate (only down-link communications and payload do not scale under these circumstances). The missions that can be handled by the real-time control and operation of a set of small, semi-autonomous, interacting, behavior-controlled planetary rovers are discussed.
NASA and JPL have developed a testbed 'planetary rover' vehicle with sufficient power supplies, sensors, and computational resources for the demonstration of semiautonomous navigation. Attention is presently given to this vehicle's vision-based navigation techniques. The proposed design and its variants allow advantage to be taken of enormous quantities of both spatial and temporal information that are normally wasted, by sampling very fine detail over the full focal plane area to precisely determine those parts of the image that are accurately at the focus range of the pinhole array used. This should generate accurate and reliable real-time range information in a wide variety of natural scenes, with little or no computation.
The paper presents two path planners suitable for planetary rovers. The first is based on fuzzy description of the terrain, and genetic algorithm to find a traversable path in a rugged terrain. The second planner uses a global optimization method with a cost function that is the path distance divided by the velocity limit obtained from the consideration of the rover static and dynamic stability. A description of both methods is provided, and the results of paths produced are given which show the effectiveness of the path planners in finding near optimal paths. The features of the methods and their suitability and application for rover path planning are compared
This paper presents an new strategy for autonomous navigation of planetary rovers using the fuzzy logic framework and novel on-board measure of terrain traversability.
The paper presents two path planners suitable for planetary rovers. The first is based on fuzzy description of the terrain, and genetic algorithm to find a traversable path in a rugged terrain.
The evolution of NASA's planning for planetary rovers (that is robotic vehicles which may be deployed on planetary bodies for exploration, science analysis, and construction) and some of the technology that was developed to achieve the desired capabilities is reviewed. The program is comprised of a variety of vehicle sizes and types in order to accommodate a range of potential user needs. This includes vehicles whose weight spans a few kilograms to several thousand kilograms; whose locomotion is implemented using wheels, tracks, and legs; and whose payloads vary from microinstruments to large scale assemblies for construction. Robotic vehicles and their associated control systems, developed in the late 1980's as part of a proposed Mars Rover Sample Return (MRSR) mission, are described. Goals suggested at the time for such a MRSR mission included navigating for one to two years across hundreds of kilometers of Martian surface; traversing a diversity of rugged, unknown terrain; collecting and analyzing a variety of samples; and bringing back selected samples to the lander for return to Earth. Current plans (considerably more modest) which have evolved both from technological 'lessons learned' in the previous period, and modified aspirations of NASA missions are presented. Some of the demonstrated capabilities of the developed machines and the technologies which made these capabilities possible are described.
The report discusses the: Decentralized Control of Markov Decision Processes. Study the complexity of decentralized control of Markov decision processes, and develop algorithms for finding optimal control policies. Scheduling Contract Algorithms. Develop an optimal method for scheduling runs of a contract anytime algorithm (one that takes the deadline as input) in situations where the deadline is unknown, multiple problem instances must be solved, and a multi-processor machine is available. Planetary Rover Control as a Markov Decision Process.Use the Markov decision process framework to formalize and solve problems in planetary rover control. Adaptive Peer Selection. Use reinforcement learning to maximize the expected down-load speed for a client in a peer-to-peer file sharing system.