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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

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NASA NTRS1994

Control of a Serpentine Robot for Inspection Tasks

This paper presents a simple and robust kinematic control scheme for the JPL serpentine robot system. The proposed strategy is developed using the dampened-least-squares/configuration control methodology, and permits the considerable dexterity of the JPL serpentine robot to be effectively utilized for maneuvering in the congested and uncertain workspaces often encountered in inspection tasks. Computer simulation results are given for the 20 degree-of-freedom (DOF) manipulator system obtained by mounting the twelve DOF serpentine robot at the end-effector of an eight DOF Robotics Research arm/lathe-bed system. These simulations demonstrate that the proposed approach provides an effective method of controlling this complex system.

robotics simulations kinematic control serpentine ↗

NASA NTRS2008

The Telesupervised Adaptive Ocean Sensor Fleet (TAOSF) Architecture: Coordination of Multiple Oceanic Robot Boats

Earth science research must bridge the gap between the atmosphere and the ocean to foster understanding of Earth s climate and ecology. Ocean sensing is typically done with satellites, buoys, and crewed research ships. The limitations of these systems include the fact that satellites are often blocked by cloud cover, and buoys and ships have spatial coverage limitations. This paper describes a multi-robot science exploration software architecture and system called the Telesupervised Adaptive Ocean Sensor Fleet (TAOSF). TAOSF supervises and coordinates a group of robotic boats, the OASIS platforms, to enable in-situ study of phenomena in the ocean/atmosphere interface, as well as on the ocean surface and sub-surface. The OASIS platforms are extended deployment autonomous ocean surface vehicles, whose development is funded separately by the National Oceanic and Atmospheric Administration (NOAA). TAOSF allows a human operator to effectively supervise and coordinate multiple robotic assets using a sliding autonomy control architecture, where the operating mode of the vessels ranges from autonomous control to teleoperated human control. TAOSF increases data-gathering effectiveness and science return while reducing demands on scientists for robotic asset tasking, control, and monitoring. The first field application chosen for TAOSF is the characterization of Harmful Algal Blooms (HABs). We discuss the overall TAOSF architecture, describe field tests conducted under controlled conditions using rhodamine dye as a HAB simulant, present initial results from these tests, and outline the next steps in the development of TAOSF.

sensor web↗

NASA NTRS2013

In-Situ Operations and Planning for the Mars Science Laboratory Robotic Arm: The First 200 Sols

The Robotic Arm (RA) has operated for more than 200 Martian solar days (or sols) since the Mars Science Laboratory rover touched down in Gale Crater on August 5, 2012. During the first seven months on Mars the robotic arm has performed multiple contact science sols including the positioning of the Alpha Particle X-Ray Spectrometer (APXS) and/or Mars Hand Lens Imager (MAHLI) with respect to rocks or loose regolith targets. The RA has supported sample acquisition using both the scoop and drill, sample processing with CHIMRA (Collection and Handling for In- Situ Martian Rock Analysis), and delivery of sample portions to the observation tray, and the SAM (Sample Analysis at Mars) and CHEMIN (Chemistry and Mineralogy) science instruments. This paper describes the planning and execution of robotic arm activities during surface operations, and reviews robotic arm performance results from Mars to date.

Mars surface operations↗

NASA NTRS1992

Automation and Robotics for Space-Based Systems, 1991

A NASA Langley workshop on Automation and Robotics for Space-Based Systems was held on December 10, 1991. This conference proceedings document presents the overhead slides from each speaker at this event. The purpose of this in-house workshop was to assess the state-of-the-art of automation and robotics for space operations from a LaRC perspective and to identify areas of opportunity for future research. The workshop was sponsored by the Guidance, Navigation, and Control Technical Committee, chaired by Mr. Raymond C. Montgomery. Nineteen talks were given, reflecting a high level of interest in the field of automation at NASA Langley. Over half of the presentations came from the Automation Technology Branch, covering telerobotic control, EVA and IVA robotics, hand controllers for teleoperation, sensors, neural networks, and automated structural assembly, all applied to space missions. Other talks covered RMS active damping augmentation, space crane work, modeling, simulation, and control of large, flexible space manipulators, and virtual passive controller designs for space robots.

Automation↗

NASA NTRS2001

Analysis and experiments with an elephant's trunk robot

The area of tentacle and trunk type biological manipulation is not new, but there has been little progress in the development and application of a physical device to simulate these types of manipulation. Our research in this area is based on using an 'elephant trunk' robot. In this paper, we review the construction of the robot and how it compares to biological manipulators. We then apply our previously designed kinematic model to describe the kinematics of the robot. We finish by providing some examples of motion planning and intelligent manipulation using the robot.

Non-NASA Center↗

NASA NTRS2004

Robots and humans: synergy in planetary exploration

How will humans and robots cooperate in future planetary exploration? Are humans and robots fundamentally separate modes of exploration, or can humans and robots work together to synergistically explore the solar system? It is proposed that humans and robots can work together in exploring the planets by use of telerobotic operation to expand the function and usefulness of human explorers, and to extend the range of human exploration to hostile environments. Published by Elsevier Ltd.

Robotics↗

NASA NTRS1995

Robot Motion Planning Among Moving Obstacles

An on-line method is presented for computing the motion of a robot in a dynamic environment subject to the robot dynamics and its actuator constraints. This method is based on the concept of Velocity Obstacle that defines the set of robot velocities that would result in a collision between the robot and a moving obstacle. The problem of motion planning in dynamic environments is addressed.

Robotics Velocity Obstacle↗

NASA NTRS1994

A Mobile Robot for Remote Response to Incidents Involving Hazardous Materials

This paper will describe a teleoperated mobile robot system being developed at JPL for use by the JPL Fire Department/HAZMAT Team. The project, which began in October 1990, is focused on prototyping a robotic vehicle which can be quickly deployed and easily operated by HAZMAT Team personnel allowing remote entry and exploration of a hazardous material incident site. The close involvement of JPL Fire Department personnel has been critical in establishing system requirements as well as evaluating the system. The current robot, called HAZBOT III, has been especially designed for operation in environments that may contain combustible gases. Testing of the system with the Fire Department has shown that teleoperated robots can successfully gain access to incident sites allowing hazardous material spills to be remotely located and identified. Work is continuing to enable more complex missions through enhancement of the operator interface and by allowing tetherless operation.

robots teleoperator hazardous materials HAZMAT HAZ↗

NASA NTRS2005

Planning to fail: mission design for modular repairable robot teams

This paper presents a method using stochastic simulation to evaluate the reliability of robot teams consisting of modular robots. For an example planetary exploration mission we use this method to compare the performance of a repairable robot team with spare modules versus nonrepairable robot teams.

mission planning↗

NASA NTRS2006

JPL Robotics

Goal: Develop new robotic technologies Groups: a) Robotic Hardware Systems; b) Robotic Software Systems; c) Mobility and Manipulation; d) Computer Vision; e) Advanced Robotic Controls

education↗

NASA NTRS2014

Design and Control of Compliant Tensegrity Robots Through Simulation and Hardware Validation

To better understand the role of tensegrity structures in biological systems and their application to robotics, the Dynamic Tensegrity Robotics Lab at NASA Ames Research Center has developed and validated two different software environments for the analysis, simulation, and design of tensegrity robots. These tools, along with new control methodologies and the modular hardware components developed to validate them, are presented as a system for the design of actuated tensegrity structures. As evidenced from their appearance in many biological systems, tensegrity ("tensile-integrity") structures have unique physical properties which make them ideal for interaction with uncertain environments. Yet these characteristics, such as variable structural compliance, and global multi-path load distribution through the tension network, make design and control of bio-inspired tensegrity robots extremely challenging. This work presents the progress in using these two tools in tackling the design and control challenges. The results of this analysis includes multiple novel control approaches for mobility and terrain interaction of spherical tensegrity structures. The current hardware prototype of a six-bar tensegrity, code-named ReCTeR, is presented in the context of this validation.

Robotics↗

NASA NTRS2017

Human-Robot Teaming: Communication, Coordination, and Collaboration

In this talk, I will describe how NASA Ames has been studying how human-robot teams can increase the performance, reduce the cost, and increase the success of a variety of endeavors. The central premise of our work is that humans and robots should support one another in order to compensate for limitations of automation and manual control. This principle has broad applicability to a wide range of domains, environments, and situations. At the same time, however, effective human-robot teaming requires communication, coordination, and collaboration -- all of which present significant research challenges. I will discuss some of the ways that NASA Ames is addressing these challenges and present examples of our work involving planetary rovers, free-flying robots, and self-driving cars.

robotics↗

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 NTRS2024

MAGIK Animation of Robotic Operations for Flight SpaceX-30 to ISS

The MAGIK Robotic analysis team provides kinematic feasibility assessments for the ISS and has produced an animation to evaluate Extravehicular Robotics (EVR) activities for the SpaceX (SpX)-30 flight. Shown EVR activities are preliminary and final operations will be developed by Flight Operations Directorate (FOD) Robotics (ROBO). The animation also displays the current ISS configuration at the time of the flight. Flight SpX-30 includes a SpaceX Cargo Dragon vehicle docked to Node 2 Zenith (N2Z) International Docking Adapter (IDA) and consists of the delivery of the Pump Module (PM) Integrated Assembly (IA). Robotic operations shown include the Special Purpose Dexterous Manipulator (SPDM) based on the Space Station Remote Manipulator System (SSRMS) for Trunk extraction of the PM IA, maneuvering to the External Stowage Platform 3 (ESP-3), temporary removal of the Control Moment Gyro (CMG) from ESP-3 Site 4, install of the PM IA at ESP-3 Site 3 and re-install of the CMG to ESP-3 Site4. There is no disposal payload for this flight.

ISS↗

NASA NTRS2024

MAGIK Animation of Robotic Operations for Flight SpaceX-31 to ISS

The MAGIK Robotics analysis team provides kinematic feasibility assessments for the ISS and has produced an animation to showcase Extravehicular Robotics (EVR) activities for Flight SpaceX (SpX)-31. Shown EVR activities were developed by Flight Operations Directorate (FOD) Robotics (ROBO). The animation also displays the current ISS configuration at the time of the flight in Increment 72. Flight SpX-31 includes a SpaceX Cargo Dragon vehicle docked to Node 2 Forward (N2F) and consists of the delivery of the Coronal Observation Experiment (CODEX) payload. Robotic operations shown include utilization the Special Purpose Dexterous Manipulator (SPDM) based on the Space Station Remote Manipulator System (SSRMS), survey of the cargo trunk, extraction of CODEX from the trunk, stow of SPDM, SSRMS walkoff to the Mobile Remote Servicer (MRS) Base System (MBS), SSRMS grapple of SPDM, translate of the Mobile Transporter (MT), and install of CODEX to Express Logistics Carrier 3 (ELC-3) Site 3. There is no disposal payload for this flight.

ISS↗

NASA NTRS1977

Robot learning and error correction

A model of robot learning is described that associates previously unknown perceptions with the sensed known consequences of robot actions. For these actions, both the categories of outcomes and the corresponding sensory patterns are incorporated in a knowledge base by the system designer. Thus the robot is able to predict the outcome of an action and compare the expectation with the experience. New knowledge about what to expect in the world may then be incorporated by the robot in a pre-existing structure whether it detects accordance or discrepancy between a predicted consequence and experience. Errors committed during plan execution are detected by the same type of comparison process and learning may be applied to avoiding the errors.

Friedman, L.↗

NASA NTRS1976

Robot Display and Control program (ROBDAC)

The ROBOT display and control program (ROBDAC) to be written for the Adage 340 computer is designed to communicate with the Univac 1110 computer with the aid of the graphic support communications programs. ROBDAC and the Adage computer act as an input/output device for the program ROBOT, which is run on the Univac 1110. ROBDAC controls the input to ROBOT by displaying images of the inputs, providing an editing technique for these inputs, shipping the input data to the Univac, and then commanding ROBOT to start execution. The output is done in a similar manner after receiving the output data from the Univac. This data will be displayed numerically as well as by plotted graphs. All of the input/output will be done interactively with practically 'finger tip' control. A general program flow diagram of ROBDAC is included.

Stewart, W. A.↗

NASA NTRS1979

Machine intelligence and robotics: Report of the NASA study group. Executive summary

A brief overview of applications of machine intelligence and robotics in the space program is given. These space exploration robots, global service robots to collect data for public service use on soil conditions, sea states, global crop conditions, weather, geology, disasters, etc., from Earth orbit, space industrialization and processing technologies, and construction of large structures in space. Program options for research, advanced development, and implementation of machine intelligence and robot technology for use in program planning are discussed. A vigorous and long-range program to incorporate and keep pace with state of the art developments in computer technology, both in spaceborne and ground-based computer systems is recommended.

Source record↗