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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

High precision control and deep learning-based corn stand counting algorithms for agricultural robot

This paper presents high precision control and deep learning-based corn stand counting algorithms for a low-cost, ultra-compact 3D printed and autonomous field robot for agricultural operations. Currently, plant traits, such as emergence rate, biomass, vigor, and stand counting, are measured manually. This is highly labor-intensive and prone to errors. The robot, termed TerraSentia, is designed to automate the measurement of plant traits for efficient phenotyping as an alternative to manual measurements. In this paper, we formulate a Nonlinear Moving Horizon Estimator that identifies key terrain parameters using onboard robot sensors and a learning-based Nonlinear Model Predictive Control that ensures high precision path tracking in the presence of unknown wheel-terrain interaction. Moreover, we develop a machine vision algorithm designed to enable an ultra-compact ground robot to count corn stands by driving through the fields autonomously. The algorithm leverages a deep network to detect corn plants in images, and a visual tracking model to re-identify detected objects at different time steps. We collected data from 53 corn plots in various fields for corn plants around 14 days after emergence (stage V3 - V4). The robot predictions have agreed well with the ground truth with C robot =1.02×C human -0.86 and a correlation coefficient R=0.96. The mean relative error given by the algorithm is -3.78%, and the standard deviation is 6.76%. These results indicate a first and significant step towards autonomous robot-based real-time phenotyping using low-cost, ultra-compact ground robots for corn and potentially other crops.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1994

An intelligent robotic aid system for human services

The long term goal of our research at the Intelligent Robotic Laboratory at Vanderbilt University is to develop advanced intelligent robotic aid systems for human services. As a first step toward our goal, the current thrusts of our R&D are centered on the development of an intelligent robotic aid called the ISAC (Intelligent Soft Arm Control). In this paper, we describe the overall system architecture and current activities in intelligent control, adaptive/interactive control and task learning.

Kawamura, K.↗
NASA NTRS1989

Extracting text from real-world scenes

Many scenes contain significant textual information that can be extremely helpful for understanding and/or navigation. For example, text-based information can frequently be the primary cure used for navigating inside buildings. A subject might first read a marquee, then look for an appropriate hallway and walk along reading door signs and nameplates until the destination is found. Optical character recognition has been studied extensively in recent years, but has been applied almost exclusively to printed documents. As these techniques improve it becomes reasonable to ask whether they can be applied to an arbitrary scene in an attempt to extract text-based information. Before an automated system can be expected to navigate by reading signs, however, the text must first be segmented from the rest of the scene. This paper discusses the feasibility of extracting text from an arbitrary scene and using that information to guide the navigation of a mobile robot. Considered are some simple techniques for first locating text components and then tracking the individual characters to form words and phrases. Results for some sample images are also presented.

Bixler, J. Patrick↗
NASA NTRS2005

Robotic and Human-Tended Collaborative Drilling Automation for Subsurface Exploration

Future in-situ lunar/martian resource utilization and characterization, as well as the scientific search for life on Mars, will require access to the subsurface and hence drilling. Drilling on Earth is hard - an art form more than an engineering discipline. Human operators listen and feel drill string vibrations coming from kilometers underground. Abundant mass and energy make it possible for terrestrial drilling to employ brute-force approaches to failure recovery and system performance issues. Space drilling will require intelligent and autonomous systems for robotic exploration and to support human exploration. Eventual in-situ resource utilization will require deep drilling with probable human-tended operation of large-bore drills, but initial lunar subsurface exploration and near-term ISRU will be accomplished with lightweight, rover-deployable or standalone drills capable of penetrating a few tens of meters in depth. These lightweight exploration drills have a direct counterpart in terrestrial prospecting and ore-body location, and will be designed to operate either human-tended or automated. NASA and industry now are acquiring experience in developing and building low-mass automated planetary prototype drills to design and build a pre-flight lunar prototype targeted for 2011-12 flight opportunities. A successful system will include development of drilling hardware, and automated control software to operate it safely and effectively. This includes control of the drilling hardware, state estimation of both the hardware and the lithography being drilled and state of the hole, and potentially planning and scheduling software suitable for uncertain situations such as drilling. Given that Humans on the Moon or Mars are unlikely to be able to spend protracted EVA periods at a drill site, both human-tended and robotic access to planetary subsurfaces will require some degree of standalone, autonomous drilling capability. Human-robotic coordination will be important, either between a robotic drill and humans on Earth, or a human-tended drill and its visiting crew. The Mars Analog Rio Tinto Experiment (MARTE) is a current project that studies and simulates the remote science operations between an automated drill in Spain and a distant, distributed human science team. The Drilling Automation for Mars Exploration (DAME) project, by contrast: is developing and testing standalone automation at a lunar/martian impact crater analog site in Arctic Canada. The drill hardware in both projects is a hardened, evolved version of the Advanced Deep Drill (ADD) developed by Honeybee Robotics for the Mars Subsurface Program. The current ADD is capable of 20m, and the DAME project is developing diagnostic and executive software for hands-off surface operations of the evolved version of this drill. The current drill automation architecture being developed by NASA and tested in 2004-06 at analog sites in the Arctic and Spain will add downhole diagnosis of different strata, bit wear detection, and dynamic replanning capabilities when unexpected failures or drilling conditions are discovered in conjunction with simulated mission operations and remote science planning. The most important determinant of future 1unar and martian drilling automation and staffing requirements will be the actual performance of automated prototype drilling hardware systems in field trials in simulated mission operations. It is difficult to accurately predict the level of automation and human interaction that will be needed for a lunar-deployed drill without first having extensive experience with the robotic control of prototype drill systems under realistic analog field conditions. Drill-specific failure modes and software design flaws will become most apparent at this stage. DAME will develop and test drill automation software and hardware under stressful operating conditions during several planned field campaigns. Initial results from summer 2004 tests show seven identifi distinct failure modes of the drill: cuttings-removal issues with low-power drilling into permafrost, and successful steps at executive control and initial automation.

Glass, Brian↗
NASA NTRSDate not supplied

Astrobee's Multi-year Activities at the International Space Station's Japanese Experimental Module

The Astrobee free-flying robots recently completed their third successful year of operations, housed in the Japanese Experimental Module (JEM) on the International Space Station. We summarize the three years of operation, giving special attention to JAXA's 1st and 2nd Kibo Robot Programming Challenge (RPC) and the mapping processes and tools that make Astrobees' autonomous operation possible. The JEM is an ever changing, dynamic environment where light settings, cargo, payloads, and crew members constantly move and interact with one another. The 1st JAXA Kibo RPC event, a collaboration between JAXA and NASA, was held in 2020. Students from several countries in the Asia-Pacific region competed in programming challenges with a simulated Astrobee. The finalists were then invited to run their code on an actual Astrobee in the JEM. For the final round, students programmed Astrobee to visit three different locations to obtain data that would instruct the robot to complete a final task with the participation of ISS crew. The first competition was a tremendous success, leading to an equally successful 2nd JAXA Kibo RPC in 2021 with even larger participation. The 3rd JAXA Kibo RPC will occur in 2022 expanding further to incorporate US participants. These activities led to several firsts in Astrobee’s history: operation of an Astrobee free-flying robot without crew supervision in preparation for on-orbit operations, autonomous image acquisition towards updates of the navigation map, non-NASA code running on the robot (both from JAXA and participating students), two heterogeneous free-flying robots from two different space agencies working together (Int-Ball and Astrobee) during the final event in 2020, the first payload using Astrobee, and having Astrobee controlled from a non-NASA location (Tsukuba Space Center). The preparation towards these activities involved constant evaluation of the different components of Astrobee's systems, specially mapping and localization. The paper describes the evolution of these systems such as the improvements made in localization to reduce localization drift by using graph-based optimization instead of the extended Kalman Filter localizer. Additionally, it reports on the mapping process and analysis tools created to validate map consistency across different activities in the constantly changing JEM environment. These enhancements have enabled the Astrobee facility to successfully execute over 100 ISS activities supporting over a dozen researchers and partners around the world.

Astrobee↗
DOE OSTI2018

Soft Robotic Glove System for Wearable Haptic Teleoperation - 18373

Managing nuclear waste is a difficult, dangerous, and costly task. Teleoperation of robotic operators is an important functionality for this application, allowing robotic devices to operate in dangerous environments while still leveraging the existing abilities and technical knowledge of human workers. One difficulty in implementing effective teleoperation systems is that human operators rely on more senses beside sight: in particular, touch. The sense of touch could provide significant benefits for teleoperation, preventing environmental mishaps that could cost millions of dollars. To help remedy this problem, we present a soft haptic feedback glove system. The primary functionality of this system is to provide tactile and force feedback on the user's hands. This was achieved using custom cylindrical pneumatic actuators. These actuators consist of plastic sheeting folded into a hollow-walled cylinder which is connected to a pressure source. When pressurized, the cylinder walls expand and the cylinder straightens, with the force being related to the pressure. The glove system has one of these actuators over each of the user's three main fingers (index, middle, and thumb), where pressurizing the actuator applies a reaction force to the finger of the user, mimicking the resistance of a grasped object. The expansion of these actuators also causes them to physically press against the user's fingers, giving them the feeling of contact. To demonstrate the usability of this system, we implemented a virtual environment in V-REP simulating the interactions between a robotic Jaco Arm and a floating ball. This simulation receives hand and figure positions from the haptic glove and used them to drive the state of the simulated Jaco Arm. In response to the interactions between the Jaco and the floating ball, the simulation returns commands to the glove, instructing it to pressurize or depressurize its actuators as appropriate, allowing the user to feel the ball in their hand. We tested users in their ability to prevent the ball from floating away using this system with and without the haptic feedback. Results show that the addition of haptic feedback significantly improved the ability of users to interact precisely with the environment. We also used the finger positions of the haptic glove to control a physical robotic hand, and demonstrated the system's usability for control of real robots, though the lack of sensors on the robot made providing the tactile feedback impractical. However, there is more to grasping and holding an object than just the feeling of contact and the resistance to closing one's hand. The weight of the object will apply forces to the user's other joints as they hold it. To this end, we added a haptic feedback device for the user's wrist, a technique that can be generalized to the user's other joints. This is made up of reverse Pneumatic Artificial Muscles (rPAMs) stretching across the wrist between mounts on the hand and forearm. These rPAM actuators are tubes of silicone wrapped in thread such that they extend when pressurized. This extension can apply torque on the user's wrist, mimicking the feeling of gravity, or allowing the simulation of additional contact forces (such as the user's hand impacting an object). We tested this wrist device independently using a simulated path-following experiment. Users showed a significant improvement in performance when aided by haptic feedback during sinusoidal path experiments, demonstrating the usability of this approach. We then integrated the two systems, further demonstrating the usability of this approach. This project represents the first step towards a more effective robotic teleoperation system, allowing skilled human workers to perform tasks more effectively while remaining out of danger. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS2021

InSight Mars Lander Instrument Deployment Arm Flight Software

The Interior Exploration using Seismic Investigations, Geodesy and Heat Transport (InSight) lander landed on Mars on November 26, 2018 and continues to investigate the internal structure of the planet two years later. The Instrument Deployment Arm (IDA), a robotic arm on the lander, was used to deploy the science instrument payloads from the lander deck to the surface of Mars and to take images of the lander and the surrounding environment. This was the first precision deployment and release by a robotic arm on another planet. After deploying the instruments, the IDA has been used for instrument commissioning, scientific data gathering, and to assist with troubleshooting one of the science instruments. This paper provides a high-level summary of the flight software that controls the IDA. The paper provides an overview of the IDA software interfaces, task structure, command handling strategy, motion specification, motion planning, motor control, grapple control, fault protection, and telemetry.

Ali, Khaled S.↗
NASA NTRS2005

Predictive Interfaces for Long-Distance Tele-Operations

We address the development of predictive tele-operator interfaces for humanoid robots with respect to two basic challenges. Firstly, we address automating the transition from fully tele-operated systems towards degrees of autonomy. Secondly, we develop compensation for the time-delay that exists when sending telemetry data from a remote operation point to robots located at low earth orbit and beyond. Humanoid robots have a great advantage over other robotic platforms for use in space-based construction and maintenance because they can use the same tools as astronauts do. The major disadvantage is that they are difficult to control due to the large number of degrees of freedom, which makes it difficult to synthesize autonomous behaviors using conventional means. We are working with the NASA Johnson Space Center's Robonaut which is an anthropomorphic robot with fully articulated hands, arms, and neck. We have trained hidden Markov models that make use of the command data, sensory streams, and other relevant data sources to predict a tele-operator's intent. This allows us to achieve subgoal level commanding without the use of predefined command dictionaries, and to create sub-goal autonomy via sequence generation from generative models. Our method works as a means to incrementally transition from manual tele-operation to semi-autonomous, supervised operation. The multi-agent laboratory experiments conducted by Ambrose et. al. have shown that it is feasible to directly tele-operate multiple Robonauts with humans to perform complex tasks such as truss assembly. However, once a time-delay is introduced into the system, the rate of tele\ioperation slows down to mimic a bump and wait type of activity. We would like to maintain the same interface to the operator despite time-delays. To this end, we are developing an interface which will allow for us to predict the intentions of the operator while interacting with a 3D virtual representation of the expected state of the robot. The predictive interface anticipates the intention of the operator, and then uses this prediction to initiate appropriate sub-goal autonomy tasks.

Wheeler, Kevin R.↗
DOE OSTI2013

Adaptive Control Parameters for Dispersal of Multi-Agent Mobile Ad Hoc Network (MANET) Swarms

A mobile ad hoc network is a collection of independent nodes that communicate wirelessly with one another. This paper investigates nodes that are swarm robots with communications and sensing capabilities. Each robot in the swarm may operate in a distributed and decentralized manner to achieve some goal. This paper presents a novel approach to dynamically adapting control parameters to achieve mesh configuration stability. The presented approach to robot interaction is based on spring force laws (attraction and repulsion laws) to create near-optimal mesh like configurations. In prior work, we presented the extended virtual spring mesh (EVSM) algorithm for the dispersion of robot swarms. This paper extends the EVSM framework by providing the first known study on the effects of adaptive versus static control parameters on robot swarm stability. The EVSM algorithm provides the following novelties: 1) improved performance with adaptive control parameters and 2) accelerated convergence with high formation effectiveness. Simulation results show that 120 robots reach convergence using adaptive control parameters more than twice as fast as with static control parameters in a multiple obstacle environment.

42 ENGINEERING↗
DOE OSTI2019

Automated species-level identification of planktic foraminifera using convolutional neural networks, with comparison to human performance

Picking foraminifera from sediment samples is an essential, but repetitive and low-reward task that is well-suited for automation. The first step toward building a picking robot is the development of an automated identification system. We use machine learning techniques to train convolutional neural networks (CNNs) to identify six species of extant planktic foraminifera that are widely used by paleoceanographers, and to distinguish the six species from other taxa. We employ CNNs that were previously built and trained for image classification. Foraminiferal training and identification use reflected light microscope digital images taken at 16 different illumination angles using a light-emitting diode (LED) ring. Overall machine accuracy, as a combination of precision and recall, is better than 80% even with limited training. We compare machine performance to that of human pickers (six experts and five novices) by tasking each with the identification of 540 specimens based on images. Experts achieved comparable precision but poorer recall relative to the machine, with an average accuracy of 63%. Novices scored lower than experts on both precision and recall, for an overall accuracy of 53%. The machine achieved fairly uniform performance across the six species, while participants' scores were strongly species-dependent, commensurate with their past experience and expertise. The machine was also less sensitive to specimen orientation (umbilical versus spiral views) than the humans. Finally, these results demonstrate that our approach can provide a versatile ‘brain’ for an eventual automated robotic picking system.

58 GEOSCIENCES↗
NASA NTRS1987

Planning and scheduling for robotic assembly

A system for reasoning about robotic assembly tasks is described. The first element of this system is a facility for itemizing the constraints which determine the admissible orderings over the activities to be sequenced. The second element is a facility which partitions the activities into independent subtasks and produces a set of admissible strategies for each. Finally, the system has facilities for constructing an admissible sequence of activities which is consistent with the given constraints. This can be done off-line, in advance of task execution, or it can be done incrementally, at execution time, according to conditions in the execution environment. The language of temporal constraints and the methods of inference presented in related papers are presented. It is shown how functional and spatial relationships between components impose temporal constraints on the order of assembly and how temporal constraints then imply admissible strategies and feasible sequences.

Fox, Barry R.↗
NASA NTRS1987

Space Station flight telerobotic servicer functional requirements development

The Space Station flight telerobotic servicer (FTS), a flight robotic system for use on the first Space Station launch, is described. The objectives of the FTS program include: (1) the provision of an alternative crew EVA by supporting the crew in assembly, maintenance, and servicing activities, and (2) the improvement of crew safety by performing hazardous tasks such as spacecraft refueling or thermal and power system maintenance. The NASA/NBS Standard Reference Model provides the generic, hierarchical, structured functional control definition for the system. It is capable of accommodating additional degrees of machine intelligence in the future.

Oberright, John↗
NASA NTRS1993

Planning collision free paths for two cooperating robots using a divide-and-conquer C-space traversal heuristic

A method was developed to plan feasible and obstacle-avoiding paths for two spatial robots working cooperatively in a known static environment. Cooperating spatial robots as referred to herein are robots which work in 6D task space while simultaneously grasping and manipulating a common, rigid payload. The approach is configuration space (c-space) based and performs selective rather than exhaustive c-space mapping. No expensive precomputations are required. A novel, divide-and-conquer type of heuristic is used to guide the selective mapping process. The heuristic does not involve any robot, environment, or task specific assumptions. A technique was also developed which enables solution of the cooperating redundant robot path planning problem without requiring the use of inverse kinematics for a redundant robot. The path planning strategy involves first attempting to traverse along the configuration space vector from the start point towards the goal point. If an unsafe region is encountered, an intermediate via point is identified by conducting a systematic search in the hyperplane orthogonal to and bisecting the unsafe region of the vector. This process is repeatedly applied until a solution to the global path planning problem is obtained. The basic concept behind this strategy is that better local decisions at the beginning of the trouble region may be made if a possible way around the 'center' of the trouble region is known. Thus, rather than attempting paths which look promising locally (at the beginning of a trouble region) but which may not yield overall results, the heuristic attempts local strategies that appear promising for circumventing the unsafe region.

Weaver, Johnathan M.↗
NASA NTRS1994

Task-level control for autonomous robots

Task-level control refers to the integration and coordination of planning, perception, and real-time control to achieve given high-level goals. Autonomous mobile robots need task-level control to effectively achieve complex tasks in uncertain, dynamic environments. This paper describes the Task Control Architecture (TCA), an implemented system that provides commonly needed constructs for task-level control. Facilities provided by TCA include distributed communication, task decomposition and sequencing, resource management, monitoring and exception handling. TCA supports a design methodology in which robot systems are developed incrementally, starting first with deliberative plans that work in nominal situations, and then layering them with reactive behaviors that monitor plan execution and handle exceptions. To further support this approach, design and analysis tools are under development to provide ways of graphically viewing the system and validating its behavior.

Simmons, Reid↗
NASA NTRS1991

VERDEX: A virtual environment demonstrator for remote driving applications

One of the key areas of the National Advanced Robotics Centre's enabling technologies research program is that of the human system interface, phase 1 of which started in July 1989 and is currently addressing the potential of virtual environments to permit intuitive and natural interactions between a human operator and a remote robotic vehicle. The aim of the first 12 months of this program (to September, 1990) is to develop a virtual human-interface demonstrator for use later as a test bed for human factors experimentation. This presentation will describe the current state of development of the test bed, and will outline some human factors issues and problems for more general discussion. In brief, the virtual telepresence system for remote driving has been designed to take the following form. The human operator will be provided with a helmet-mounted stereo display assembly, facilities for speech recognition and synthesis (using the Marconi Macrospeak system), and a VPL DataGlove Model 2 unit. The vehicle to be used for the purposes of remote driving is a Cybermotion Navmaster K2A system, which will be equipped with a stereo camera and microphone pair, mounted on a motorized high-speed pan-and-tilt head incorporating a closed-loop laser ranging sensor for camera convergence control (currently under contractual development). It will be possible to relay information to and from the vehicle and sensory system via an umbilical or RF link. The aim is to develop an interactive audio-visual display system capable of presenting combined stereo TV pictures and virtual graphics windows, the latter featuring control representations appropriate for vehicle driving and interaction using a graphical 'hand,' slaved to the flex and tracking sensors of the DataGlove and an additional helmet-mounted Polhemus IsoTrack sensor. Developments planned for the virtual environment test bed include transfer of operator control between remote driving and remote manipulation, dexterous end effector integration, virtual force and tactile sensing (also the focus of a current ARRL contract, initially employing a 14-pneumatic bladder glove attachment), and sensor-driven world modeling for total virtual environment generation and operator-assistance in remote scene interrogation.

Stone, Robert J.↗
NASA NTRS2006

Launching to the Moon, Mars, and Beyond

The U.S. Vision for Space Exploration, announced in 2004, calls on NASA to finish constructing the International Space Station, retire the Space Shuttle, and build the new spacecraft needed to return to the Moon and go on the Mars. By exploring space, America continues the tradition of great nations who mastered the Earth, air, and sea, and who then enjoyed the benefits of increased commerce and technological advances. The progress being made today is part of the next chapter in America's history of leadership in space. In order to reach the Moon and Mars within the planned timeline and also within the allowable budget, NASA is building upon the best of proven space transportation systems. Journeys to the Moon and Mars will require a variety of vehicles, including the Ares I Crew Launch Vehicle, the Ares V Cargo Launch Vehicle, the Orion Crew Exploration Vehicle, and the Lunar Surface Access Module. What America learns in reaching for the Moon will teach astronauts how to prepare for the first human footprints on Mars. While robotic science may reveal information about the nature of hydrogen on the Moon, it will most likely tale a human being with a rock hammer to find the real truth about the presence of water, a precious natural resource that opens many possibilities for explorers. In this way, the combination of astronauts using a variety of tools and machines provides a special synergy that will vastly improve our understanding of Earth's cosmic neighborhood.

Dumbacher, Daniel L.↗
NASA NTRS2007

Observing Mode Attitude Controller for the Lunar Reconnaissance Orbiter

The Lunar Reconnaissance Orbiter (LRO) mission is the first of a series of lunar robotic spacecraft scheduled for launch in Fall 2008. LRO will spend at least one year in a low altitude polar orbit around the Moon, collecting lunar environment science and mapping data to enable future human exploration. The LRO employs a 3-axis stabilized attitude control system (ACS) whose primary control mode, the "Observing mode", provides Lunar Nadir, off-Nadir, and Inertial fine pointing for the science data collection and instrument calibration. The controller combines the capability of fine pointing with that of on-demand large angle full-sky attitude reorientation into a single ACS mode, providing simplicity of spacecraft operation as well as maximum flexibility for science data collection. A conventional suite of ACS components is employed in this mode to meet the pointing and control objectives. This paper describes the design and analysis of the primary LRO fine pointing and attitude re-orientation controller function, known as the "Observing mode" of the ACS subsystem. The control design utilizes quaternion feedback, augmented with a unique algorithm that ensures accurate Nadir tracking during large angle yaw maneuvers in the presence of high system momentum and/or maneuver rates. Results of system stability analysis and Monte Carlo simulations demonstrate that the observing mode controller can meet fine pointing and maneuver performance requirements.

Calhourn, Philip C.↗
NASA NTRS1999

Multifunction automated crawling system

The present invention is an automated crawling robot system including a platform, a first leg assembly, a second leg assembly, first and second rails attached to the platform, and an onboard electronic computer controller. The first leg assembly has an intermittent coupling device and the second leg assembly has an intermittent coupling device for intermittently coupling the respective first and second leg assemblies to a particular object. The first and second leg assemblies are slidably coupled to the rail assembly and are slidably driven by motors to thereby allow linear movement. In addition, the first leg assembly is rotary driven by a rotary motor to thereby provide rotary motion relative to the platform. To effectuate motion, the intermittent coupling devices of the first and second leg assemblies alternately couple the respective first and second leg assemblies to an object. This motion is done while simultaneously moving one of the leg assemblies linearly in the desired direction and preparing the next step. This arrangement allows the crawler of the present invention to traverse an object in a range of motion covering 360 degrees.

Bar-Cohen, Yoseph↗