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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.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Ground Simulation of an Autonomous Satellite Rendezvous and Tracking System Using Dual Robotic Systems

A hardware-in-the-loop ground system was developed for simulating a robotic servicer spacecraft tracking a target satellite at short range. A relative navigation sensor package "Argon" is mounted on the end-effector of a Fanuc 430 manipulator, which functions as the base platform of the robotic spacecraft servicer. Machine vision algorithms estimate the pose of the target spacecraft, mounted on a Rotopod R-2000 platform, relay the solution to a simulation of the servicer spacecraft running in "Freespace", which performs guidance, navigation and control functions, integrates dynamics, and issues motion commands to a Fanuc platform controller so that it tracks the simulated servicer spacecraft. Results will be reviewed for several satellite motion scenarios at different ranges. Key words: robotics, satellite, servicing, guidance, navigation, tracking, control, docking.

Trube, Matthew J.↗
NASA NTRS2019

Artificial Intelligence: Powering Human Exploration of the Moon and Mars

Artificial Intelligence (AI) is a growing field of computa- tional science techniques designed to mimic functions per- formed by people. Advancements in autonomy will depend on a portfolio of AI technologies. Automated planning and scheduling is a venerable field of study in AI, and is needed for a variety of mission planning functions. Plan execution technology is less well studied, but important for auton- omy and robotics. Specialized forms of automated reason- ing and machine learning are key technologies to enable fault management. Over the past decade, the NASA Au- tonomous Systems and Operations (ASO) project has devel- oped and demonstrated numerous autonomy enabling tech- nologies employing AI techniques. Our work has employed AI in three distinct ways to enable autonomous mission op- erations capabilities. Crew Autonomy gives astronauts tools to assist in the performance of each of these mission oper-ations functions. Vehicle System Management uses AI tech- niques to turn the astronaut's spacecraft into a robot, allow- ing it to operate when astronauts are not present, or to reduce astronaut workload. AI technology also enables Autonomous Robots as crew assistants or proxies when the crew are not present. When these capabilities are used to enable astro- nauts to operate autonomously, they must be integrated with user interfaces, introducing numerous human factors con- siderations; when these capabilities are used to enable vehi- cle system management, they must be integrated with flight software, and run on embedded processors under the control of real-time operating systems.We first describe human spaceflight mission operations capabilities. The remainder of the paper will describe the ASO project, and the development and demonstration per- formed by ASO since 2011. We will describe the AI tech- niques behind each of these demonstrations, which include a variety of symbolic automated reasoning and machine learn- ing based approaches. Finally, we conclude with an assess- ment of future development needs for AI to enable NASA's future Exploration missions.

Mission Operations↗
NASA NTRS2017

Supervisory Control of a Humanoid Robot in Microgravity for Manipulation Tasks

Teleoperation is the dominant form of dexterous robotic tasks in the field. However, there are many use cases in which direct teleoperation is not feasible such as disaster areas with poor communication as posed in the DARPA Robotics Challenge, or robot operations on spacecraft a large distance from Earth with long communication delays. Presented is a solution that combines the Affordance Template Framework for object interaction with TaskForce for supervisory control in order to accomplish high level task objectives with basic autonomous behavior from the robot. TaskForce, is a new commanding infrastructure that allows for optimal development of task execution, clear feedback to the user to aid in off-nominal situations, and the capability to add autonomous verification and corrective actions. This framework has allowed the robot to take corrective actions before requesting assistance from the user. This framework is demonstrated with Robonaut 2 removing a Cargo Transfer Bag from a simulated logistics resupply vehicle for spaceflight using a single operator command. This was executed with 80% success with no human involvement, and 95% success with limited human interaction. This technology sets the stage to do any number of high level tasks using a similar framework, allowing the robot to accomplish tasks with minimal to no human interaction.

Farrell, Logan C.↗
NASA NTRS2016

Design of an Excavation Robot: Regolith Advanced Surface Systems Operations Robot (RASSOR) 2.0

To continue on a sustainable and flexible path, NASA needs to address the challenge of collecting and moving large amounts of regolith at the destination. Acquiring the water resources on Mars will require mining significant quantities of regolith and this is not possible with the state-of-the-art low mass excavation systems. Low gravity environments (Mars = 3/8 G) and launch mass restrictions limit the traction and the resulting reaction force of the vehicle, making current terrestrial techniques impractical. This project addressed this challenge by developing a completely new technology that can mine large quantities of regolith on Mars. Recent measurements by the “Curiosity” rover on Mars have found that the regolith contains ~ 2% water by weight globally, ~4% in Jezero Crater (Human Architecture Team’s reference landing site), and much more at the poles(Leshin et al, 2013). RASSOR 2.0 is a planetary excavator, which has a mass of 66 kg, with a 0.38 kg vehicle mass per kilogram, per hour of excavation rate and power usage of 4 W per kg of regolith excavation rate. A single RASSOR 2.0 can excavate a minimum of 2.7 metric tons of regolith per day.This is accomplished by using counteracting excavation forces on two opposing digging implements called bucket drums and an autonomous mining control system. This work has addressed several major research areas outlined in the NASA Technology Area (TA) 04 Robotics & Autonomous Systems and TA 07 Human Destination Systems roadmaps. This project started at Technology Readiness Level (TRL) 4 as a low fidelity “proof of concept” prototype which has successfully demonstrated basic regolith simulant excavation functionality in a lab-scale gravity off load test. The foundational technology described here was awarded US patent number: US 9027265 for a “Zero horizontal reaction force excavator” on May 12, 2015.

RASSOR↗
NASA NTRS2008

Automated and Adaptive Mission Planning for Orbital Express

The Orbital Express space mission was a Defense Advanced Research Projects Agency (DARPA) lead demonstration of on-orbit satellite servicing scenarios, autonomous rendezvous, fluid transfers of hydrazine propellant, and robotic arm transfers of Orbital Replacement Unit (ORU) components. Boeing's Autonomous Space Transport Robotic Operations (ASTRO) vehicle provided the servicing to the Ball Aerospace's Next Generation Serviceable Satellite (NextSat) client. For communication opportunities, operations used the high-bandwidth ground-based Air Force Satellite Control Network (AFSCN) along with the relatively low-bandwidth GEO-Synchronous space-borne Tracking and Data Relay Satellite System (TDRSS) network. Mission operations were conducted out of the RDT&E Support Complex (RSC) at the Kirtland Air Force Base in New Mexico. All mission objectives were met successfully: The first of several autonomous rendezvous was demonstrated on May 5, 2007; autonomous free-flyer capture was demonstrated on June 22, 2007; the fluid and ORU transfers throughout the mission were successful. Planning operations for the mission were conducted by a team of personnel including Flight Directors, who were responsible for verifying the steps and contacts within the procedures, the Rendezvous Planners who would compute the locations and visibilities of the spacecraft, the Scenario Resource Planners (SRPs), who were concerned with assignment of communications windows, monitoring of resources, and sending commands to the ASTRO spacecraft, and the Mission planners who would interface with the real-time operations environment, process planning products and coordinate activities with the SRP. The SRP position was staffed by JPL personnel who used the Automated Scheduling and Planning ENvironment (ASPEN) to model and enforce mission and satellite constraints. The lifecycle of a plan began three weeks outside its execution on-board. During the planning timeframe, many aspects could change the plan, causing the need for re-planning. These variable factors, ranging from shifting contact times to ground-station closures and required maintenance times, are discussed along with the flexibility of the ASPEN tool to accommodate changes to procedures and the daily or long-range plan, which contributed to the success of the mission. This paper will present an introduction to ASPEN, a more in-depth discussion on its use on the Orbital Express mission, and other relative work. A description of ground operations after the SRP deliveries were made is included, and we briefly discuss lessons learned from the planning perspective and future work.

scheduling↗
NASA NTRS1990

Teleautonomous guidance for mobile robots

Teleautonomous guidance (TG), a technique for the remote guidance of fast mobile robots, has been developed and implemented. With TG, the mobile robot follows the general direction prescribed by an operator. However, if the robot encounters an obstacle, it autonomously avoids collision with that obstacle while trying to match the prescribed direction as closely as possible. This type of shared control is completely transparent and transfers control between teleoperation and autonomous obstacle avoidance gradually. TG allows the operator to steer vehicles and robots at high speeds and in cluttered environments, even without visual contact. TG is based on the virtual force field (VFF) method, which was developed earlier for autonomous obstacle avoidance. The VFF method is especially suited to the accommodation of inaccurate sensor data (such as that produced by ultrasonic sensors) and sensor fusion, and allows the mobile robot to travel quickly without stopping for obstacles.

Borenstein, J.↗
NASA NTRS2005

Learning for autonomous navigation : extrapolating from underfoot to the far field

Autonomous off-road navigation of robotic ground vehicles has important applications on Earth and in space exploration. Progress in this domain has been retarded by the limited lookahead range of 3-D sensors and by the difficulty of preprogramming systems to understand the traversability of the wide variety of terrain they can encounter. Enabling robots to learn from experience may alleviate both of these problems. We define two paradigms for this, learning from 3-D geometry and learning from proprioception, and describe initial instantiations of them we have developed under DARPA and NASA programs. Field test results show promise for learning traversability of vegetated terrain, learning to extend the lookahead range of the vision system, and learning how slip varies with slope.

autonomous robots↗
NASA NTRS1994

A smart telerobotic system driven by monocular vision

A robotic system that accepts autonomously generated motion and control commands is described. The system provides images from the monocular vision of a camera mounted on a robot's end effector, eliminating the need for traditional guidance targets that must be predetermined and specifically identified. The telerobotic vision system presents different views of the targeted object relative to the camera, based on a single camera image and knowledge of the target's solid geometry.

Defigueiredo, R. J. P.↗
NASA NTRS1990

The real-time learning mechanism of the Scientific Research Associates Advanced Robotic System (SRAARS)

Scientific research associates advanced robotic system (SRAARS) is an intelligent robotic system which has autonomous learning capability in geometric reasoning. The system is equipped with one global intelligence center (GIC) and eight local intelligence centers (LICs). It controls mainly sixteen links with fourteen active joints, which constitute two articulated arms, an extensible lower body, a vision system with two CCD cameras and a mobile base. The on-board knowledge-based system supports the learning controller with model representations of both the robot and the working environment. By consecutive verifying and planning procedures, hypothesis-and-test routines and learning-by-analogy paradigm, the system would autonomously build up its own understanding of the relationship between itself (i.e., the robot) and the focused environment for the purposes of collision avoidance, motion analysis and object manipulation. The intelligence of SRAARS presents a valuable technical advantage to implement robotic systems for space exploration and space station operations.

Chen, Alexander Y.↗
NASA NTRSDate not supplied

Autonomous Ocean World Exploration: Advancement of a Software Testbed

The search for life signs and potentially habitable bodies in our solar system and beyond is one of NASA’s top priorities. The prime destinations for such exploration are bodies containing liquid water, such as Jupiter’s moon Europa and Saturn’s moon Enceladus. Initial missions to these “ocean worlds” will be robotic, and because of long communication lags and blackouts, harsh environments, and limited battery life, a high degree of onboard autonomy will be required. To this end NASA has developed the Ocean Worlds Autonomy Testbed for Exploration, Research, and Simulation (OceanWATERS), a software testbed for surface mission autonomy. Under grants from NASA’s Autonomous Robotics Research for Ocean Worlds (ARROW) and Concepts for Ocean worlds Life Detection Technology (COLDTech) programs, collectively 6 research teams at universities and companies across the United States have developed autonomy solutions using OceanWATERS, tackling a variety of surface mission challenges and employing state-of-the-art AI-based solutions. This paper provides a self-contained high-level description of OceanWATERS while detailing enhancements made since its 2020 release. It provides a high-level summary of the projects undertaken by participants in the ARROW and COLDTech programs and how these efforts have helped shape OceanWATERS. Finally, potential future work and directions for the testbed are listed.

K Michael Dalal↗
NASA NTRS2005

Single-Command Approach and Instrument Placement by a Robot on a Target

AUTOAPPROACH is a computer program that enables a mobile robot to approach a target autonomously, starting from a distance of as much as 10 m, in response to a single command. AUTOAPPROACH is used in conjunction with (1) software that analyzes images acquired by stereoscopic cameras aboard the robot and (2) navigation and path-planning software that utilizes odometer readings along with the output of the image-analysis software. Intended originally for application to an instrumented, wheeled robot (rover) in scientific exploration of Mars, AUTOAPPROACH could be adapted to terrestrial applications, notably including the robotic removal of land mines and other unexploded ordnance. A human operator generates the approach command by selecting the target in images acquired by the robot cameras. The approach path consists of multiple legs. Feature points are derived from images that contain the target and are thereafter tracked to correct odometric errors and iteratively refine estimates of the position and orientation of the robot relative to the target on successive legs. The approach is terminated when the robot attains the position and orientation required for placing a scientific instrument at the target. The workspace of the robot arm is then autonomously checked for self/terrain collisions prior to the deployment of the scientific instrument onto the target.

Huntsberger, Terrance↗
NASA NTRS1994

Interactive autonomy and robotic skills

Current concepts of robot-supported operations for space laboratories (payload servicing, inspection, repair, and ORU exchange) are mainly based on the concept of 'interactive autonomy' which implies autonomous behavior of the robot according to predefined timelines, predefined sequences of elementary robot operations and within predefined world models supplying geometrical and other information for parameter instantiation on the one hand, and the ability to override and change the predefined course of activities by human intervention on the other hand. Although in principle a very powerful and useful concept, in practice the confinement of the robot to the abstract world models and predefined activities appears to reduce the robot's stability within real world uncertainties and its applicability to non-predefined parts of the world, calling for frequent corrective interaction by the operator, which in itself may be tedious and time-consuming. Methods are presented to improve this situation by incorporating 'robotic skills' into the concept of interactive autonomy.

Kellner, A.↗
NASA NTRS1990

A robotic return to the moon

The autonomous lunar precursor mission presently proposed for low cost manned revisits to the lunar surface, designated 'Lunar Oasis by Automation and Robotics', employs two self-similar robotic vehicles, and three experimental 'biovolumes' which are directly derived from the lunar landers that are initially entrusted with fulfilling mission hardware-delivery requirements. The two vehicles would support the experimental biovolumes by returning resources for use in physicochemical or biological processing. Delivered resources would be combined with those in situ to furnish reconfigured biovolumes with the capabilities for autonomous biological growth and wastes-reprocessing demonstrations.

Luttges, Marvin W.↗
NASA NTRS2016

Localization from Visual Landmarks on a Free-Flying Robot

We present the localization approach for Astrobee,a new free-flying robot designed to navigate autonomously on board the International Space Station (ISS). Astrobee will conduct experiments in microgravity, as well as assisst astronauts and ground controllers. Astrobee replaces the SPHERES robots which currently operate on the ISS, which were limited to operating in a small cube since their localization system relied on triangulation from ultrasonic transmitters. Astrobee localizes with only monocular vision and an IMU, enabling it to traverse the entire US segment of the station. Features detected on a previously-built map, optical flow information,and IMU readings are all integrated into an extended Kalman filter (EKF) to estimate the robot pose. We introduce several modifications to the filter to make it more robust to noise.Finally, we extensively evaluate the behavior of the filter on atwo-dimensional testing surface.

Coltin, Brian↗
NASA NTRS2001

Instrument technologies for the detection of extraterrestrial intersteller robotic probes.

In the continuing endeavor to detect evidence of ETI (Extraterrestrial Intelligence) in the solar neighborhood, instrument technologies now exist that allow the formation of a scientific method to carry out a search for interstellar robotic probes of possible extraterrestrial origin. The range of currently observable probe features/manifestations will be shown and how they influence search space, instrument selection and deployment. Autonomous instrument platforms (i.e. robotic observatories) to search for anomalous energy signatures can be designed and assembled using Commercial off-the-shelf (COTS) hardware and software. The COTS approach to observatory design provides an economical, flexible and robust path toward collecting reliable data. The present variety of COTS instruments permits the necessary observational sensitivity , bandwidth and embedded processing speed to establish a nearby robotic probe detection envelope. A survey of these instrument technologies will be presented and how they can be applied to the challenge of collecting enough scientific data on anomalous observational phenomena to determine whether or not a robotic probe was detected

Stride, Scot Lloyd↗
NASA NTRS1992

Bilevel Shared Control Of A Remote Robotic Manipulator

Proposed concept blends autonomous and teleoperator control modes, each overcoming deficiencies of the other. Both task-level and execution-level functions performed at local and remote sites. Applicable to systems with long communication delay between local and remote sites or systems intended to function partly autonomously.

Hayati, Samad A.↗
NASA NTRS2020

Investigating Relationships Between Geochemistry and Physical Grain Characteristics Along a Glacio-Fluvial-Aeolian Sediment Transport Pathway Using µXRF

Iceland’s basaltic volcanic rocks and glacial, fluvial, and aeolian landscapes resemble those studied on Mars, which makes it an ideal location to study the evolution of basaltic landscapes, the weathering and alteration of basaltic sediments in cold and wet environments, and the generation of a basaltic sedimentary record. The SAND-E: Semi-Autonomous Navigation for Detrital Environments project examines physical and chemical changes in sediments transported through basaltic fluvial and aeolian environments, and tests operational scenarios, which include a drone and a robotic rover instrumented with autonomous terrain analysis software. As part of the SAND-E project, we examined a glacial outwash plain at Skjaldbreiðauhraun, in SW Iceland. This study uses micro X-ray fluorescence (μXRF) to examine the chemical and physical properties of unconsolidated sediment-size fractions from 710 μm to < 63 μm along a downstream transect from a glacial sourced watershed. μXRF is ideally suited for this task because it maps elemental distributions at sub-grain scales thereby allowing a direct correlation between grainsize, grain shape, and chemistry. It is also a good analog technique for the Mars 2020 mission equipped with the PIXL (Planetary Instrument for X-ray Lithochemistry) that will be deployed at Jezero Crater, Mars.

Champion, E.↗
NASA NTRS2018

Conceptual Ideas for Radio Telescope on the Far Side of the Moon

A radio telescope on the far-side of the Moon has tremendous advantages compared to Earth-based telescopes because it could observe the universe at wavelengths that are hitherto poorly explored by humans so far and the Moon acts as a physical shield that isolates the telescope from the radio interference and noises from Earth. This paper presents a novel concept for building a radio telescope on the far-side of the Moon. The main idea is to shape a suitable existing lunar crater (1 − 50km in diameter) on the far-side of the Moon into a spherical reflecting dish. The proposed Lunar Crater Radio Telescope (LCRT) would be able to observe the universe in the 5 − 100m wavelength band (i.e., 3 − 60MHz radio frequency band). The key innovations of this concept are: (1) LCRT would be the largest filled-aperture radio telescope in the Solar System. (2) LCRT could potentially make tremendous scientific discoveries in fields of cosmology and extrasolar planets by observing the universe in the 5−100m λ band(i.e., 3−60MHz ν band) that has been hitherto poorly explored. (3) It would require only a few robots from Earth and autonomously modify an existing lunar crater to build the LCRT; thereby significantly reducing launch weight and cost compared to all previous lunar surface telescope mission concepts. (4) Furthermore, the Earth based robots are not consumed during construction of LCRT. Therefore, they could create a network of LCRTs to (i) observe different regions of the universe, and (ii) enable lunar Very-Long-Baseline Interferometry (VLBI) astronomy. We envisage that this concept would unlock the potential for groundbreaking scientific discoveries in radio astronomy.

Rahmani, Amir↗