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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Regolith Advanced Surface Systems Operations Robot (RASSOR) Phase 2 and Smart Autonomous Sand-Swimming Excavator

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Phase 2 is an excavation robot for mining regolith on a planet like Mars. The robot is programmed using the Robotic Operating System (ROS) and it also uses a physical simulation program called Gazebo. This internship focused on various functions of the program in order to make it a more professional and efficient robot. During the internship another project called the Smart Autonomous Sand-Swimming Excavator was worked on. This is a robot that is designed to dig through sand and extract sample material. The intern worked on programming the Sand-Swimming robot, and designing the electrical system to power and control the robot.

Regolith↗
NASA NTRSDate not supplied

Space Robot Operating System (Space ROS)

Space Robot Operating System (Space ROS) is an open-source software framework for flight-quality robotic and autonomous space systems. It combines the benefits of open-source software and flight software best-practices into a single framework. Space ROS is predicated on ROS2 and is therefore reusable, modular and adoptable. As an open-source framework, it is accessible to the global space community. Space ROS is intended to be compliant with NASA flight software engineering practices in order to facilitate meeting mission and safety standards. Space ROS has fault management and real-time capabilities at its core.

Will Chambers↗
NASA NTRS2015

RASSOR - Regolith Advanced Surface Systems Operations Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) is a lightweight excavator for mining in reduced gravity. RASSOR addresses the need for a lightweight (<100 kg) robot that is able to overcome excavation reaction forces while operating in reduced gravity environments such as the moon or Mars. A nominal mission would send RASSOR to the moon to operate for five years delivering regolith feedstock to a separate chemical plant, which extracts oxygen from the regolith using H2 reduction methods. RASSOR would make 35 trips of 20 kg loads every 24 hours. With four RASSORs operating at one time, the mission would achieve 10 tonnes of oxygen per year (8 t for rocket propellant and 2 t for life support). Accessing craters in space environments may be extremely hard and harsh due to volatile resources - survival is challenging. New technologies and methods are required. RASSOR is a product of KSC Swamp Works which establishes rapid, innovative and cost effective exploration mission solutions by leveraging partnerships across NASA, industry and academia.

Regolith↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU)processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRSDate not supplied

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensory. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗
NASA NTRS2013

Regolith Advanced Surface Systems Operations Robot Excavator

The Regolith Advanced Surface Systems Operations Robot (RASSOR) excavator robot is a teleoperated mobility platform with a space regolith excavation capability. This more compact, lightweight design (<50 kg) has counterrotating bucket drums, which results in a net-zero reaction horizontal force due to the self-cancellation of the symmetrical, equal but opposing, digging forces.

Mueller, Robert P.↗
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 NTRS1990

The Flight Telerobotic Servicer (FTS) NASA's first operational robotic system

NASA has completed the preliminary definition phase of the Flight Telerobotic Servicer (FTS) and is now preparing to begin the detailed design and fabrication phase. The FTS will be designed and built by Martin Marietta Astronautics Group in Denver, CO, for the Goddard Space Flight Center, in support of the Space Station Freedom Program. The design concepts for the FTS are discussed, as well as operational scenarios for the assembly, maintenance, servicing and inspection tasks which are being considered for the FTS. The upcoming Development Test Flight (DTF-1) is the first of two shuttle test flights to test FTS operations in the environment of space and to demonstrate the FTS capabilities in performing tasks for Space Station Freedom. Operational planning for DTF-1 is discussed as well as development plans for the operational support of the FTS on the space station.

Andary, J.↗
NASA NTRS2012

Regolith Advanced Surface Systems Operations Robot (RASSOR)

Regolith is abundant on extra-terrestrial surfaces and is the source of many resources such as oxygen, hydrogen, titanium, aluminum, iron, silica and other valuable materials, which can be used to make rocket propellant, consumables for life support, radiation protection barrier shields, landing pads, blast protection berms, roads, habitats and other structures and devices. Recent data from the Moon also indicates that there are substantial deposits of water ice in permanently shadowed crater regions and possibly under an over burden of regolith. The key to being able to use this regolith and acquire the resources, is being able to manipulate it with robotic excavation and hauling machinery that can survive and operate in these very extreme extra-terrestrial surface environments. In addition, the reduced gravity on the Moon, Mars, comets and asteroids poses a significant challenge in that the necessary reaction force for digging cannot be provided by the robot's weight as is typically done on Earth. Space transportation is expensive and limited in capacity, so small, lightweight payloads are desirable, which means large traditional excavation machines are not a viable option. A novel, compact and lightweight excavation robot prototype for manipulating, excavating, acquiring, hauling and dumping regolith on extra-terrestrial surfaces has been developed and tested. Lessons learned and test results will be presented including digging in a variety of lunar regolith simulant conditions including frozen regolith mixed with water ice.

Mueller, Robert P.↗
NASA NTRSDate not supplied

Space ROS - ACO: Space Robot Operating System

Space ROS is a matured version of ROS 2 using flight software engineering practices to facilitate mission- and safety-critical applications. Our goal is to reduce the barrier to maturation and infusion of software developed using the popular ROS framework.

Austin Breien Probe↗
NASA NTRS1992

A distributed telerobotics system for space operations

Robotic systems for space operations will require a combination of teleoperation, closely supervised autonomy, and loosely supervised autonomy. They may involve multiple robots, multiple controlling sites, and long communication delays. We have constructed a distributed telerobotics system as a framework for studying these problems. Our system is based on a modular interconnection scheme which allows the components of either manual or autonomous control systems to communicate and share information. It uses a wide area network to connect robots and operators at several different sites. This presentation will describe the structure of our system, the components used in our configurations, and results of some of our teleoperation experiments.

Wise, James D.↗
NASA NTRS2013

Basic Operational Robotics Instructional System

The Basic Operational Robotics Instructional System (BORIS) is a six-degree-of-freedom rotational robotic manipulator system simulation used for training of fundamental robotics concepts, with in-line shoulder, offset elbow, and offset wrist. BORIS is used to provide generic robotics training to aerospace professionals including flight crews, flight controllers, and robotics instructors. It uses forward kinematic and inverse kinematic algorithms to simulate joint and end-effector motion, combined with a multibody dynamics model, moving-object contact model, and X-Windows based graphical user interfaces, coordinated in the Trick Simulation modeling environment. The motivation for development of BORIS was the need for a generic system for basic robotics training. Before BORIS, introductory robotics training was done with either the SRMS (Shuttle Remote Manipulator System) or SSRMS (Space Station Remote Manipulator System) simulations. The unique construction of each of these systems required some specialized training that distracted students from the ideas and goals of the basic robotics instruction.

Todd, Brian Keith↗
NASA NTRS2006

The Human-Robot Interaction Operating System

In order for humans and robots to work effectively together, they need to be able to converse about abilities, goals and achievements. Thus, we are developing an interaction infrastructure called the "Human-Robot Interaction Operating System" (HRI/OS). The HRI/OS provides a structured software framework for building human-robot teams, supports a variety of user interfaces, enables humans and robots to engage in task-oriented dialogue, and facilitates integration of robots through an extensible API.

Fong, Terrence↗
DOE OSTI2020

TORONE: Total Characterisation by Remote Observation of Nuclear Environments - 20591

This paper describes the autonomous robotic systems developed in the TORONE project (Total Characterisation by Remote Observation of Nuclear Environments) for combined characterisation by remote techniques in nuclear environments. There are four main components to the system. Firstly, robot operation which uses a Robot Operating System (ROS) allowing ease of communication between hardware and software alongside robot vision systems such as Lidar and/or photogrammetry. Secondly, radiation detection instrumentation for gamma and neutron sources which is also collimated for spatial resolution. Thirdly, photonic characterisation instrumentation for remote material identification by means of Raman spectroscopy and Laser induced breakdown spectroscopy (LIBS). Finally, a data management system is described which contains the TORONE characterisation data with the ability to overlay material characterisation information onto 3D maps of the nuclear environment. Preliminary results are described alongside discussion of some of the synergies of the combined approach. There are many applications of such an autonomous system in nuclear decommissioning, waste management and asset management. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Performance Evaluation of Augmented Teleoperation of Contact Manipulation Tasks

At Argonne National Laboratory, an enhanced telerobotic concept has been suggested by providing augmented virtual fixtures for precise and dexterous manipulation. The proposed technology incorporated a human-robot interface that can assist personnel on the processes of Deactivation and Decommissioning in sites of high radiation. It has been implemented on a dual-arm robot system, known as Baxter, by integrating the Robotic Operating System (ROS) with 3D sensors and visual-haptic operator interface. However, what remained before its practical utilization is the capability for precisely placing the virtual fixtures. To this end, the objectives involved camera calibration, which required hardware fabrication and setup, as well as modification and implementation of ROS. The goal of this Research and Development is to develop an augmented-reality- based operator interface for human-inclusive, intelligent, and autonomous robotic system for the Deactivation and Decommissioning (D and D) of radioactive sites. The objectives are to develop: Collaborative Robot; Multi-modal Mixed-Reality Human-Robot Interface; Intelligent and Autonomous Behaviors. In order to achieve this, Baxter's Head-Kinect camera and Left-Hand camera need to be calibrated to overlap the real environment with the simulated environment. Camera calibration, which is crucial for precisely placing the virtual fixtures, was successful after running the simulations. The real and simulated environments overlapped, permitting the utilization of augmented teleoperation and the dexterous manipulation of Baxter for D and D applications in nuclear sites. Future steps: Performance evaluation of augmented teleoperation of contact manipulation tasks: Multiple-Camera 3D Reconstruction and Automation. Oculus Interface: Augmented reality and machine learning for enhanced telerobotic operation (Augmented Tele-autonomy): Machine-learning techniques for complex and flexible autonomous robotic behaviors. Interactive remote operation of robotic systems. Mesh cutting with simulation and real robot.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

WM26 Paper Multi-Robot Collaboration for Hazardous Environments

Hazardous nuclear and industrial facilities are rarely designed for robots. Work in these domains demand precise manipulation and robust mobility in cluttered, constrained spaces where off-the-shelf platforms struggle and “one-size-fits-all” machines become costly and complex. Idaho National Laboratory (INL) is developing an autonomous, multi-robot inspection system that coordinates task-specific platforms rather than relying on a single omni-tool robot. An electric truck serves as a power and compute hub for a custom manipulator co-developed with Florida International University (FIU), a commercial mini crawler, a pan–tilt–zoom camera, and a Nexxis Argus LiDAR mapping system. Working in concert, these robots generate spatial, radiation, and temperature maps of the pit environments at the Hanford Waste Tank Farms. These systems will capture visual records and environmental telemetry to allow for analysis post inspection. The system architecture uses Robot Operating System 2 (ROS 2) for publish/subscribe integration, NVIDIA Isaac Sim and Unity for simulation and visualization, and algorithms such as NVBlox to fuse data into unified 3D overlays. This robot-agnostic approach reduces operator burden by enabling autonomy across heterogeneous platforms and lets each robot be used where it is strongest. Having autonomous functions means operators don’t have to fully control multiple different components. The ease of use could allow for more widespread adoption of advanced robotics at waste management sites that see continued use. By coordinating simpler, purpose-built mechanisms, the approach lowers design and manufacturing complexity, reduces capital risk in contaminated settings, and improves controllability for complex inspection and manipulation tasks. We present the architecture, early results, and lessons learned from building and deploying this coordinated multi-robot system, with the goal of accelerating safe, cost-effective adoption of advanced robotics at waste-management sites.

42 - ENGINEERING↗