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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Experimental Facility to Measure Power and Forces to Excavate Lunar Regolith Simulants

An Excavation Lab has been built at the NASA Glenn Research Center in support of the NASA In-Situ Resource Utilization (ISRU) program objectives to measure the power and forces needed to excavate granular lunar regolith. The data obtained will be used to validate excavation models used in system studies and for developing light weight, energy efficient digging devices for activities on the moon and mars. The Excavation Lab houses the Advanced Planetary Excavator (APEX), an electrically actuated backhoe arm with a bucket, which is used to dig GRC-3B, a simulant of granular lunar regolith comprised of silica sand and silt. A load cell is mounted between the arm and the bucket to measure digging forces. Dig trajectories files are created and used to control the APEX for repeatability. Comparison of preliminary data recorded for the same trajectory in air and in GRC-3B shows measurable difference in power and load cell measurements. Load cell forces for a linear dig in GRC-3B are presented.

Excavation↗
NASA NTRS2012

The Montana ALE (Autonomous Lunar Excavator) Systems Engineering Report

On May 2 1-26, 20 12, the third annual NASA Lunabotics Mining Competition will be held at the Kennedy Space Center in Florida. This event brings together student teams from universities around the world to compete in an engineering challenge. Each team must design, build and operate a robotic excavator that can collect artificial lunar soil and deposit it at a target location. Montana State University, Bozeman, is one of the institutions selected to field a team this year. This paper will summarize the goals of MSU's lunar excavator project, known as the Autonomous Lunar Explorer (ALE), along with the engineering process that the MSU team is using to fulfill these goals, according to NASA's systems engineering guidelines.

Lars Osborne↗
NASA NTRS2013

Impact-Actuated Digging Tool for Lunar Excavation

NASA s plans for a lunar outpost require extensive excavation. The Lunar Surface Systems Project Office projects that thousands of tons of lunar soil will need to be moved. Conventional excavators dig through soil by brute force, and depend upon their substantial weight to react to the forces generated. This approach will not be feasible on the Moon for two reasons: (1) gravity is 1/6th that on Earth, which means that a kg on the Moon will supply 1/6 the down force that it does on Earth, and (2) transportation costs (at the time of this reporting) of $50K to $100K per kg make massive excavators economically unattractive. A percussive excavation system was developed for use in vacuum or nearvacuum environments. It reduces the down force needed for excavation by an order of magnitude by using percussion to assist in soil penetration and digging. The novelty of this excavator is that it incorporates a percussive mechanism suited to sustained operation in a vacuum environment. A percussive digger breadboard was designed, built, and successfully tested under both ambient and vacuum conditions. The breadboard was run in vacuum to more than 2..times the lifetime of the Apollo Lunar Surface Drill, throughout which the mechanism performed and held up well. The percussive digger was demonstrated to reduce the force necessary for digging in lunar soil simulant by an order of magnitude, providing reductions as high as 45:1. This is an enabling technology for lunar site preparation and ISRU (In Situ Resource Utilization) mining activities. At transportation costs of $50K to $100K per kg, reducing digging forces by an order of magnitude translates into billions of dollars saved by not launching heavier systems to accomplish excavation tasks necessary to the establishment of a lunar outpost. Applications on the lunar surface include excavation for habitats, construction of roads, landing pads, berms, foundations, habitat shielding, and ISRU.

Wilson, Jak↗
NASA NTRS2012

Lunar Excavation Experiments in Simulant Soil Test Beds-Revisiting the Surveyor Geotechnical Data

(1) Establishing ISRU technologies on planetary bodies is an important long-term goal of NASA; (2) Excavation is a key component of these ISRU processes; (3) Lack of flight data relevant to lunar excavation; (4) Existing models of the excavation-cutting phenomenon give varying results; (5) The lack of predictive models of the dynamic behavior of soils in excavation implements is a major driver for these studies; and (6) Objective: Need to develop robust models of excavation cutting phenomena that generate predictive capabilities to aid the designer and engineer.

Agui, Juan H.↗
NASA NTRSDate not supplied

Power Measurements to Excavate Lunar Soil Simulant GRC-3B Using Arc Backhoe Trajectories

Understanding, mitigating, and minimizing power and mass requirements are crucial to developing the next generation excavation technologies for lunar and planetary in-situ resource utilization (ISRU). Towards this end, electrical power to the Advanced Planetary Excavator (APEX) was measured while excavating granular lunar soil simulant GRC-3B. Using a 21.6-cm wide bucket having a 30° leading edge, arc-shaped backhoe trajectories were dug to depths of 5, 10, and 20 cm with rake angles of 10, 20, and 30 degrees. Maximum net power, net energy, net energy per mass excavated, rate of mass excavated, horizontal distance from soil entry to exit (at bucket tip), and the trajectory to bucket volume percentage are presented to inform the scientific community as trajectories and designs are planned for future missions. Using APEX’s capability to evaluate power and energy consumption of excavation tools and processes gives guidance to developing power requirements and efficient methods for lunar excavation.

Excavation↗
NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of how much mass is in the drums, this type of high-level planning is not possible. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All take in system states, such as arm/drum positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums.1) A neural network model that takes a vector of normalized system states; 2) A model that uses the integrated power consumption of an arm-raise (normalized by velocity); 3) A model that uses average drum current over a variable length interval of the drum disengaged from the surface; and 4) A real-time estimation model that aggregates excavation drum current. The developed models run in real time, outputting predictions for the front and rear drums, timestamp of the last prediction, and total mass in RASSOR’s drums. Further testing is required to validate the arm-raise model (2), though initial tests indicate reasonable performance (<10% mean error) on the hardware. The linear fit of average drum-current model (3) had a front value of r^2=0.99 and a rear value of r^2=0.98 on the validation dataset. This model currently has the best performance on unseen data. The real time model (4) is still in development, though initial results on a small subset of the training data show that it has high accuracy in predicting the increase in mass during excavation. Though work remains to be done with deploying a high-fidelity model to the physical system that makes predictions with error below the desired threshold, the modular architecture for model development allows quick adjustment of parameters to increase model fidelity. This architecture can also be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results are promising as it has been shown that models can be developed that accurately estimate excavated regolith mass.

rassor↗
NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a mobile robotic bucket-drum excavator platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for estimating the quantity of regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete In-Situ Resource Utilization (ISRU) missions. To teleoperate or run autonomously, it is crucial for the amount of regolith mass ingested to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of the total mass in the drums, this type of high-level planning is not possible. Three distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR, none of which require modification to the hardware. All take in system states, such as arm/drum motor positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums. The developed models run in real-time, outputting predictions for the front drum mass, rear drum mass, timestamp of the last prediction, and total drum mass (sum of front and rear) in RASSOR’s drums. Models deployed to the hardware have low error (<7.5% mean error over the mass range, and <2.6% mean error when drums are more than half full) when making predictions in real-time. Our modeling approach can be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results of this work are promising and show that models can be developed to accurately estimate excavated regolith mass.

Bucket Drum Excavators↗
NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a mobile robotic bucket-drum excavator platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for estimating the quantity of regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete In-Situ Resource Utilization (ISRU) missions. To teleoperate or run autonomously, it is crucial for the amount of regolith mass ingested to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of the total mass in the drums, this type of high-level planning is not possible. Three distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR, none of which require modification to the hardware. All take in system states, such as arm/drum motor positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums. The developed models run in real-time, outputting predictions for the front drum mass, rear drum mass, timestamp of the last prediction, and total drum mass (sum of front and rear) in RASSOR’s drums. Models deployed to the hardware have low error (<7.5% mean error over the mass range, and <2.6% mean error when drums are more than half full) when making predictions in real-time. Our modeling approach can be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results of this work are promising and show that models can be developed to accurately estimate excavated regolith mass.

bucket drum excavators↗
NASA NTRS2021

Mass Inferencing Model Creation And Deployment To Lunar Excavation Robot, RASSOR

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. This research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. Radio wave propagation time to the Moon and back is ~2.56 seconds. Though teleoperation is possible with this delay, autonomous capability that enables RASSOR to plan and execute excavation missions intelligently and efficiently is preferred. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation (e.g. knowledge of whether drums are full informs the task of highest priority, whether it be continuing to dig, or returning to a processing plant to offload regolith). A configurable data reduction and analysis pipeline was created to allow for straightforward incorporation of new data, such as that from lunar excavation, to improve model performance in new environments. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All four models take in system states and output a mass prediction for each set of the robot’s bucket drums. Initial results from deployment to RASSOR and testing in a simulated lunar environment show that the models have <10% mean error during robot operation. Future work includes refinement of a model that estimates regolith mass in real-time during excavation as well as further testing of the developed models on the hardware.

ROS↗
NASA NTRS1992

Mobile continuous lunar excavation

A novel approach to the concept of lunar mining and the use of in situ oxygen, metallics, and ceramics is presented. The EVA time required to set up, relocate, and maintain equipment, as well as the cost per pound of shipping the mining and processing equipment to the moon are considered. The proposed soil fracturing/loading mechanisms are all based loosely on using the Apollo Lunar Roving Vehicle (LRV) Frame. All use motor driven tracks for mobility in the forward/reverse and left/right direction. All mechanisms employ the concept of rototillers which are attached to a gantry which, through the use of motor-driven lead screws, provide the rototillers with an up/down capability. A self-reactant excavator, a local mass enhanced excavator, and a soil reactant excavator are illustrated.

Paterson, John L.↗
NASA NTRSDate not supplied

Lunar Excavator Mission Operations using Dynamic Movement Primitives

To support sustainable infrastructure on the Moon, NASA must leverage robots to extract lunar resources for in-situ processing and construction. As part of this effort, NASA is launching the in-situ resource utilization (ISRU) Pilot Excavator later this decade to validate a robotic regolith excavator based on the Regolith Advanced Surface Systems Operations Robot (RASSOR). RASSOR is designed to extract and transport regolith to meet the needs of ISRU architectures. During its mission, Pilot Excavator will be tasked with driving in test patterns to demonstrate the operational concept. One of these tests is a circular trajectory around the lander while avoiding miscellaneous surface hazards such as lunar rocks. To this end, we utilize dynamic movement primitives to represent navigation sequences as primitive trajectories. Here, we introduce a novel obstacle avoidance parameter, which is configured to avoid rocks throughout testing exercises. We demonstrate the effectiveness our method in a newly developed simulation tool called the Simulated Excavation Environment for Lunar Operations (SEELO) using models based on the NASA RASSOR 2.0 excavator. After making key changes to the obstacle avoidance formulation, our results show that the robot is able to safety and robustly navigate the lunar surface with densely populated rock obstacles while retaining the desired circle pattern behavior.

Space Robotics and Automation↗
NASA NTRS2009

Lunar Regolith Excavation Competition

The Lunar Regolith Excavation Competition is a new competition that needs graphics, logos, rules, as well as an arena. Although this is the first year of the competition, the competition is modeled after an existing competition, the Centennial Lunar Excavator Challenge. This competition however is aimed at college students. This makes the challenge identifying key aspects of the original competition and modeling them to fit into an easier task, and creating exciting advertisement that helps encourage participation. By using a youth focus group, young insight, as well as guiding advice from experts in the field, hopefully an arena can be designed and built, rules can be molded and created to fit, and alluring graphics can be printed to bring about a successful first year of the Lunar Regolith Excavation Competition.

Liles, Cassandra↗
NASA NTRS2011

A Review of Lunar Regolith Excavation Robotic Device Prototypes

The excavation of lunar regolith is desirable for use as a feedstock for oxygen production processes as well as civil engineering purposes and for the fabrication of parts and structures. This is known as In-Situ Resource Utilization (ISRU). More recently, there has been mounting evidence that water ice exists at the poles of the Moon, buried in the regolith where thermally stable conditions exist. This means that regolith excavation will be required to mine the water ice which is believed to be. mixed in with the regolith, or bonded to it. The mined water ice can then be electrolyzed to produce hydrogen and oxygen propellants which could form the basis of a cis-lunar transportation system using in-situ derived propellants. In 2007, the National Aeronautics & Space Administration (NASA) sponsored a Lunar Regolith Excavation Competition as part of its Centennial Challenges program, The competition was not won and it was held again in 2008 and 2009, when it was won by a university team. A $500,000 prize was awarded to the winning team by NASA. In 2010, NASA continued the competition as a spinoff of the Centennial Challenges, which is restricted to university participation only. This competition is known as the "Lunabotics Mining Competition" and is hosted by NASA at Kennedy Space Center. Twenty three American university teams competed in the 2010 Lunabotics Mining Competition. The competition was held again in May 2011 with over 60 teams registered, including international participation. The competition will be held again in May 2012 at Kennedy Space Center in Florida. . This paper contains a thorough review of the various regolith eX,cavation robotic device prototypes that competed in these NASA competitions, and will. classify the machines and their methods of excavation to document the variety of ideas that were spawned and built to compete at these events. It is hoped that documentation of these robots will serve to help future robotic excavation designers and provide a historical reference for future lunar mining machine endeavors.

Mueller, Robert P.↗