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All sourcesNASA NTRSDOE OSTI
NASA NTRS1997

System Wide Joint Position Sensor Fault Tolerance in Robot Systems Using Cartesian Accelerometers

Joint position sensors are necessary for most robot control systems. A single position sensor failure in a normal robot system can greatly degrade performance. This paper presents a method to obtain position information from Cartesian accelerometers without integration. Depending on the number and location of the accelerometers. the proposed system can tolerate the loss of multiple position sensors. A solution technique suitable for real-time implementation is presented. Simulations were conducted using 5 triaxial accelerometers to recover from the loss of up to 4 joint position sensors on a 7 degree of freedom robot moving in general three dimensional space. The simulations show good estimation performance using non-ideal accelerometer measurements.

Aldridge, Hal A.↗
NASA NTRS2004

The Robotic Lunar Exploration Program (RLEP): An Introduction to the Goals, Approach, and Architecture

The Vision for Space Exploration calls for undertaking lunar exploration activities to enable sustained human and robotic exploration of Mars and beyond, including more distant destinations in the solar system. In support of this vision, the Robotic Lunar Exploration Program (RLEP) is expected to execute a series of robotic missions to the Moon, starting in 2008, in order to pave the way for further human space exploration. This paper will give an introduction to the RLEP program office, its role and its goals, and the approach it is taking to executing the charter of the program. The paper will also discuss candidate architectures that are being studied as a framework for defining the RLEP missions and the context in which they will evolve.

Watzin, James G.↗
NASA NTRS2005

Interaction Challenges in Human-Robot Space Exploration

In January 2004, NASA established a new, long-term exploration program to fulfill the President's Vision for U.S. Space Exploration. The primary goal of this program is to establish a sustained human presence in space, beginning with robotic missions to the Moon in 2008, followed by extended human expeditions to the Moon as early as 2015. In addition, the program places significant emphasis on the development of joint human-robot systems. A key difference from previous exploration efforts is that future space exploration activities must be sustainable over the long-term. Experience with the space station has shown that cost pressures will keep astronaut teams small. Consequently, care must be taken to extend the effectiveness of these astronauts well beyond their individual human capacity. Thus, in order to reduce human workload, costs, and fatigue-driven error and risk, intelligent robots will have to be an integral part of mission design.

Fong, Terrence↗
NASA NTRS2005

Robot Swarms

Engineers and interns at this NASA field center are building the prototype of a robotic rover that could go where no wheeled rover has gone before-into the dark cold craters at the lunar poles and across the Moon s rugged highlands-like a walking tetrahedron. With NASA pushing to meet President Bush's new exploration objectives, the robots taking shape here today could be on the Moon in a decade. In the longer term, the concept could lead to shape-shifting robot swarms designed to explore distant planetary surfaces in advance of humans. "If you look at all of NASA s projections of the future, anyone s projections of the space program, they re all rigid-body architecture," says Steven Curtis, principal investigator on the effort. "This is not rigid-body. The whole key here is flexibility and reconfigurability with a capital R."

Morring, Frank, Jr.↗
NASA NTRS2005

Hubble Space Telescope Angular Velocity Estimation During the Robotic Servicing Mission

In 2004 NASA began investigation of a robotic servicing mission for the Hubble Space Telescope (HST). Such a mission would require estimates of the HST attitude and rates in order to achieve a capture by the proposed Hubble robotic vehicle (HRV). HRV was to be equipped with vision-based sensors, capable of estimating the relative attitude between HST and HRV. The inertial HST attitude is derived from the measured relative attitude and the HRV computed inertial attitude. However, the relative rate between HST and HRV cannot be measured directly. Therefore, the HST rate with respect to inertial space is not known. Two approaches are developed to estimate the HST rates. Both methods utilize the measured relative attitude and the HRV inertial attitude and rates. First, a non-linear estimator is developed. The nonlinear approach estimates the HST rate through an estimation of the inertial angular momentum. Second, a linearized approach is developed. The linearized approach is a pseudo-linear Kalman filter. Simulation test results for both methods are given. Even though the development began as an application for the HST robotic servicing mission, the methods presented are applicable to any rendezvous/capture mission involving a non-cooperative target spacecraft.

Thienel, Julie K.↗
NASA NTRS2005

Control Algorithms and Simulated Environment Developed and Tested for Multiagent Robotics for Autonomous Inspection of Propulsion Systems

The NASA Glenn Research Center and academic partners are developing advanced multiagent robotic control algorithms that will enable the autonomous inspection and repair of future propulsion systems. In this application, on-wing engine inspections will be performed autonomously by large groups of cooperative miniature robots that will traverse the surfaces of engine components to search for damage. The eventual goal is to replace manual engine inspections that require expensive and time-consuming full engine teardowns and allow the early detection of problems that would otherwise result in catastrophic component failures. As a preliminary step toward the long-term realization of a practical working system, researchers are developing the technology to implement a proof-of-concept testbed demonstration. In a multiagent system, the individual agents are generally programmed with relatively simple controllers that define a limited set of behaviors. However, these behaviors are designed in such a way that, through the localized interaction among individual agents and between the agents and the environment, they result in self-organized, emergent group behavior that can solve a given complex problem, such as cooperative inspection. One advantage to the multiagent approach is that it allows for robustness and fault tolerance through redundancy in task handling. In addition, the relatively simple agent controllers demand minimal computational capability, which in turn allows for greater miniaturization of the robotic agents.

Wong, Edmond↗
NASA NTRS2005

Survey of Command Execution Systems for NASA Spacecraft and Robots

NASA spacecraft and robots operate at long distances from Earth Command sequences generated manually, or by automated planners on Earth, must eventually be executed autonomously onboard the spacecraft or robot. Software systems that execute commands onboard are known variously as execution systems, virtual machines, or sequence engines. Every robotic system requires some sort of execution system, but the level of autonomy and type of control they are designed for varies greatly. This paper presents a survey of execution systems with a focus on systems relevant to NASA missions.

Verma, Vandi↗
NASA NTRS2006

Multimodal Platform Control for Robotic Planetary Exploration Missions

Planetary exploration missions pose unique problems for astronauts seeking to coordinate and control exploration vehicles. These include working in an environment filled with abrasive dust (e.g., regolith compositions), a desire to have effective hands-free communication, and a desire to have effective analog control of robotic platforms or end effectors. Requirements to operate in pressurized suits are particularly problematic due to the increased bulk and stiffness of gloves. As a result, researchers are considering alternative methods to perform fine movement control, for example capitalizing on higher-order voice actuation commands to perform control tasks. This paper presents current research at NASA s Neuro Engineering Laboratory that explores one method-direct bioelectric interpretation-for handling some of these problems. In this type of control system, electromyographic (EMG) signals are used both to facilitate understanding of acoustic speech in pressure-regulated suits 2nd to provide smooth analog control of a robotic platform, all without requiring fine-gained hand movement. This is accomplished through the use of non-invasive silver silver-chloride electrodes located on the forearm, throat, and lower chin, positioned so as to receive electrical activity originating from the muscles during contraction. For direct analog platform control, a small Personal Exploration Rover (PER) built by Carnegie Mellon University Robotics is controlled using forearm contraction duration and magnitudes, measured using several EMG channels. Signal processing is used to translate these signals into directional platform rotation rates and translational velocities. higher order commands were generated by differential contraction patterns called "clench codes."

Jorgensen, Charles↗
NASA NTRS2006

Robotic Lunar Exploration

This presentation describes current Lunar Exploration plans and objectives. It begins with specific statements from the President s vision for U.S. Space Exploration which pertain to robotic lunar missions. An outline of missions objectives is provided, along with a high-level schedule of events through the year 2025. Focus is then given to the Lunar Robotic and Precursor Program (LPRP) to describe objectives and goals. Recent developments in the Program are explained - specifically, the renaming of the RLEP program to "LPRP" and the movement of the program office to MSFC. A brief summary of the synergy expected between the robotic and crewed missions, with the LSAM descent stage Project is given. The Lunar Reconnaissance Orbiter mission, with its co-manifested Lunar Crater Observation and Sensing Satellite (LCROSS), is then described with an overview of the payloads and mission objectives. Finally, information is given about the expected future of the LPRP program and Exploration and the development of a compressive Lunar Exploration Architecture.

Echols, Raymond↗
NASA NTRS2006

Human-Robot Site Survey and Sampling for Space Exploration

NASA is planning to send humans and robots back to the Moon before 2020. In order for extended missions to be productive, high quality maps of lunar terrain and resources are required. Although orbital images can provide much information, many features (local topography, resources, etc) will have to be characterized directly on the surface. To address this need, we are developing a system to perform site survey and sampling. The system includes multiple robots and humans operating in a variety of team configurations, coordinated via peer-to-peer human-robot interaction. In this paper, we present our system design and describe planned field tests.

Fong, Terrence↗
NASA NTRS2006

NASA's Robotic Lunar Exploration Program (RLEP) 2 Mission

Before returning humans to the Moon for mankind's seventh lunar landing, NASA will embark upon a series of robotic missions to prepare the way for further exploration. These missions, part of the Robotic Lunar Exploration Program (RLEP), are designed to acquire decisive knowledge about the moon as well as to develop infrastructure needed to sustain human exploration in the lunar environment. Here we focus on the second mission in the RLEP program, RLEP-2, the first dedicated to landing in the south polar region of the moon. Managed by NASA's Marshall Space Flight Center in Huntsville, Alabama, along with the Applied Physics Laboratory and NASA Goddard Space Flight Center, RLEP-2 will build upon knowledge gained from the Chandraayan-1 and Lunar Robotic Orbiter orbital missions, to help further the prospects for sustainable human exploration on the moon. This mission will characterize the lighting environment in the polar region, critically important to understanding the amount of power available and to the thermal design of hardware, as well as explore the nature and distribution of volatiles that may be present in permanently shadowed regions of polar craters. We shall review the current status of the mission, articulate the results of onoging trade studies in power, surface mobility, launch vehicles, measurements and instrumentation, and navigation/communication, as well as discuss the primary mission objectives in detail.

Horack, John M.↗
NASA NTRS2007

Robotics

Lunar robotic functions include: 1. Transport of crew and payloads on the surface of the moon; 2. Offloading payloads from a lunar lander; 3. Handling the deployment of surface systems; with 4. Human commanding of these functions from inside a lunar vehicle, habitat, or extravehicular (space walk), with Earth-based supervision. The systems that will perform these functions may not look like robots from science fiction. In fact, robotic functions may be automated trucks, cranes and winches. Use of this equipment prior to the crew s arrival or in the potentially long periods without crews on the surface, will require that these systems be computer controlled machines. The public release of NASA's Exploration plans at the 2nd Space Exploration Conference (Houston, December 2006) included a lunar outpost with as many as four unique mobility chassis designs. The sequence of lander offloading tasks involved as many as ten payloads, each with a unique set of geometry, mass and interface requirements. This plan was refined during a second phase study concluded in August 2007. Among the many improvements to the exploration plan were a reduction in the number of unique mobility chassis designs and a reduction in unique payload specifications. As the lunar surface system payloads have matured, so have the mobility and offloading functional requirements. While the architecture work continues, the community can expect to see functional requirements in the areas of surface mobility, surface handling, and human-systems interaction as follows: Surface Mobility 1. Transport crew on the lunar surface, accelerating construction tasks, expanding the crew s sphere of influence for scientific exploration, and providing a rapid return to an ascent module in an emergency. The crew transport can be with an un-pressurized rover, a small pressurized rover, or a larger mobile habitat. 2. Transport Extra-Vehicular Activity (EVA) equipment and construction payloads. 3. Transport habitats and power modules over long distances, pre-positioning them for the arrival of crew on a subsequent lander. Surface Handling 1. Offload surface system payloads from the lander, breaking launch restraints and power/data connections. Payloads may be offloaded to a wheeled vehicle for transport. 2. Deploy payloads from a wheeled vehicle at a field site, placing the payloads in their final use site on the ground or mating them with existing surface systems. 3. Support regolith collection, site preparation, berm construction, or other civil engineering tasks using tools and implements attached to rovers. Human-Systems Interaction 1. Provide a safe command and control interface for suited EVA to ride on and drive the vehicles, making sure that the systems are also safe for working near dismounted crew. 2. Provide an effective control system for IV crew to tele-operate vehicles, cranes and other equipment from inside the surface habitats with evolving independence from Earth. .. Provide a supervisory system that allows machines to be commanded from the ground, working across the Earth-Lunar time delays on the order of 5-10 seconds (round trip) to support operations when crew are not resident on the surface. Technology Development Needs 1. Surface vehicles that can dock, align and mate with outpost equipment such as landers, habitats and fluid/power interfaces. 2. Long life motors, drive trains, seals, motor electronics, sensors, processors, cable harnesses, and dash board displays. 3. Active suspension control, localization, high speed obstacle avoidance, and safety systems for operating near dismounted crew. 4. High specific energy and specific power batteries that are safe, rechargeable, and long lived.

Ambrose, Robert O.↗
NASA NTRS2004

Architecture for robot intelligence

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a DBAM that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Peters, II, Richard Alan↗
NASA NTRS2008

Architecture for Multiple Interacting Robot Intelligences

An architecture for robot intelligence enables a robot to learn new behaviors and create new behavior sequences autonomously and interact with a dynamically changing environment. Sensory information is mapped onto a Sensory Ego-Sphere (SES) that rapidly identifies important changes in the environment and functions much like short term memory. Behaviors are stored in a database associative memory (DBAM) that creates an active map from the robot's current state to a goal state and functions much like long term memory. A dream state converts recent activities stored in the SES and creates or modifies behaviors in the DBAM.

Peters, Richard Alan, II↗
NASA NTRS2008

Vision System Measures Motions of Robot and External Objects

A prototype of an advanced robotic vision system both (1) measures its own motion with respect to a stationary background and (2) detects other moving objects and estimates their motions, all by use of visual cues. Like some prior robotic and other optoelectronic vision systems, this system is based partly on concepts of optical flow and visual odometry. Whereas prior optoelectronic visual-odometry systems have been limited to frame rates of no more than 1 Hz, a visual-odometry subsystem that is part of this system operates at a frame rate of 60 to 200 Hz, given optical-flow estimates. The overall system operates at an effective frame rate of 12 Hz. Moreover, unlike prior machine-vision systems for detecting motions of external objects, this system need not remain stationary: it can detect such motions while it is moving (even vibrating). The system includes a stereoscopic pair of cameras mounted on a moving robot. The outputs of the cameras are digitized, then processed to extract positions and velocities. The initial image-data-processing functions of this system are the same as those of some prior systems: Stereoscopy is used to compute three-dimensional (3D) positions for all pixels in the camera images. For each pixel of each image, optical flow between successive image frames is used to compute the two-dimensional (2D) apparent relative translational motion of the point transverse to the line of sight of the camera. The challenge in designing this system was to provide for utilization of the 3D information from stereoscopy in conjunction with the 2D information from optical flow to distinguish between motion of the camera pair and motions of external objects, compute the motion of the camera pair in all six degrees of translational and rotational freedom, and robustly estimate the motions of external objects, all in real time. To meet this challenge, the system is designed to perform the following image-data-processing functions: The visual-odometry subsystem (the subsystem that estimates the motion of the camera pair relative to the stationary background) utilizes the 3D information from stereoscopy and the 2D information from optical flow. It computes the relationship between the 3D and 2D motions and uses a least-mean-squares technique to estimate motion parameters. The least-mean-squares technique is suitable for real-time implementation when the number of external-moving-object pixels is smaller than the number of stationary-background pixels.

Talukder, Ashit↗
NASA NTRS2008

The Moon is a Planet Too: Lunar Science and Robotic Exploration

The first decades of the 21st century will be marked by major lunar science and exploration activities. The Moon is a witness to 4.5 billion years of solar system history, recording that history more completely and more clearly than any other planetary body. Lunar science encompasses early planetary evolution and differentiation, lava eruptions and fire fountains, impact scars throughout time, and billions of years of volatile input. I will cover the main outstanding issues in lunar science today and the most intriguing scientific opportunities made possible by renewed robotic and human lunar exploration. Barbara is a planetary scientist at NASA s Marshall Space Flight Center. She studies meteorites from the Moon, Mars and asteroids and has been to Antarctica twice to hunt for them. Barbara also works on the Mars Exploration Rovers Spirit and Opportunity and has an asteroid named after her. She is currently helping the Lunar Precursor Robotics Program on the Lunar Mapping and Modeling Project, a project tasked by the Exploration System Mission Directorate (ESMD) to develop maps and tools of the Moon to benefit the Constellation Program lunar planning. She is also supporting the Science Mission Directorate s (SMD) lunar flight projects line at Marshall as the co-chair of the Science Definition Team for NASA s next robotic landers, which will be nodes of the International Lunar Network, providing geophysical information about the Moon s interior structure and composition.

Cohen, Barbara↗
NASA NTRS2009

Adaptive Behavior for Mobile Robots

The term "System for Mobility and Access to Rough Terrain" (SMART) denotes a theoretical framework, a control architecture, and an algorithm that implements the framework and architecture, for enabling a land-mobile robot to adapt to changing conditions. SMART is intended to enable the robot to recognize adverse terrain conditions beyond its optimal operational envelope, and, in response, to intelligently reconfigure itself (e.g., adjust suspension heights or baseline distances between suspension points) or adapt its driving techniques (e.g., engage in a crabbing motion as a switchback technique for ascending steep terrain). Conceived for original application aboard Mars rovers and similar autonomous or semi-autonomous mobile robots used in exploration of remote planets, SMART could also be applied to autonomous terrestrial vehicles to be used for search, rescue, and/or exploration on rough terrain.

Huntsberger, Terrance↗
NASA NTRS2009

Monitoring and Controlling an Underwater Robotic Arm

The SSRMS Module 1 software is part of a system for monitoring an adaptive, closed-loop control of the motions of a robotic arm in NASA s Neutral Buoyancy Laboratory, where buoyancy in a pool of water is used to simulate the weightlessness of outer space. This software is so named because the robot arm is a replica of the Space Shuttle Remote Manipulator System (SSRMS). This software is distributed, running on remote joint processors (RJPs), each of which is mounted in a hydraulic actuator comprising the joint of the robotic arm and communicating with a poolside processor denoted the Direct Control Rack (DCR). Each RJP executes the feedback joint-motion control algorithm for its joint and communicates with the DCR. The DCR receives joint-angular-velocity commands either locally from an operator or remotely from computers that simulate the flight like SSRMS and perform coordinated motion calculations based on hand-controller inputs. The received commands are checked for validity before they are transmitted to the RJPs. The DCR software generates a display of the statuses of the RJPs for the DCR operator and can shut down the hydraulic pump when excessive joint-angle error or failure of a RJP is detected.

Haas, John↗