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Results for “Agricultural robotics.”

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
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↗
DOE OSTI2026

Design and Integration of a Compact Mobile Outdoor Soil Sampling Agricultural Robot

The lack of feedback on soil management for crop systems necessitates the collection of soil samples to derive insights into prevailing soil conditions. Achieving an accurate model of these plantations requires a substantial number of soil samples, which is a labor-intensive process that can suffer from inconsistencies in both the methodology of collection and the locations from which samples are gathered. In addition, the close spacing of crop rows constrains the maneuverability of mobile agricultural equipment during sample collection. This article proposes the use of agricultural robotics to facilitate the acquisition of composite soil samples with minimal human intervention, allowing for precise data collection for a Populus plant system. More specifically, this article presents a case study on the design and construction of a compact agricultural robot for soil sample collection. The performance of the robot, including its soil collection efficacy, maneuverability, and positional accuracy, is evaluated.

42 ENGINEERING↗
NASA NTRS1991

FARMS: The Flexible Agricultural Robotics Manipulator

A technology utilization project was established with the Marshall Space Flight Center and the University of Georgia to develop an Earth-based, robotic end effector to process live plant (geranium) material which will improve productivity and efficiency in agricultural systems such as commercial nurseries and greenhouse systems. The aim is to apply this technology to NASA's presence in space, including permanently manned space stations and manned planetary communities requiring large scale food production needs.

Gill, Paul S.↗
NASA NTRS1993

Robotic System For Greenhouse Or Nursery

Report presents additional information about robotic system described in "Robotic Gripper With Force Control And Optical Sensors" (MFS-28537). "Flexible Agricultural Robotics Manipulator System" (FARMS) serves as prototype of robotic systems intended to enhance productivities of agricultural assembly-line-type facilities in large commercial greenhouses and nurseries.

Gill, Paul↗
NASA NTRS1989

NASA technology applications team: Applications of aerospace technology

Two critical aspects of the Applications Engineering Program were especially successful: commercializing products of Application Projects; and leveraging NASA funds for projects by developing cofunding from industry and other agencies. Results are presented in the following areas: the excimer laser was commercialized for clearing plaque in the arteries of patients with coronary artery disease; the ultrasound burn depth analysis technology is to be licensed and commercialized; a phased commercialization plan was submitted to NASA for the intracranial pressure monitor; the Flexible Agricultural Robotics Manipulator System (FARMS) is making progress in the development of sensors and a customized end effector for a roboticized greenhouse operation; a dual robot are controller was improved; a multisensor urodynamic pressure catherer was successful in clinical tests; commercial applications were examined for diamond like carbon coatings; further work was done on the multichannel flow cytometer; progress on the liquid airpack for fire fighters; a wind energy conversion device was tested in a low speed wind tunnel; and the Space Shuttle Thermal Protection System was reviewed.

Source record↗
NASA NTRS2008

JPL Robotics Technology Applicable to Agriculture

This slide presentation describes several technologies that are developed for robotics that are applicable for agriculture. The technologies discussed are detection of humans to allow safe operations of autonomous vehicles, and vision guided robotic techniques for shoot selection, separation and transfer to growth media,

commercial off-the-shelf (COTS) hardware↗
DOE OSTI2024

Herbicide‐resistant weed management with robots: A weed ecological–economic model

The heavy reliance on herbicides for weed control has led to an increase in resistant weeds in the United States. Robotic weed control is emerging as an alternative technology for removing weeds mechanically using artificial intelligence. We develop an integrated weed ecological and economic dynamic (I‐WEED) model to examine the biophysical and economic drivers of adopting robotic weed management and simulate the optimal timing and intensity of robotic adoption within and across growing seasons. We specify a cohort‐based weed growth model that relates yield damages to effective weed density and treats the susceptibility of weeds to herbicides as a renewable resource that can be regenerated by using mechanical weeding robots, due to a fitness cost that makes resistant weeds less prolific. Compared to myopic weed management which ignores resistance development, forward‐looking management leads to earlier adoption of robots and treating robots as complements instead of substitutes to herbicides. This weed management results in adopting fewer robots, deploying robots on a smaller portion of the land, higher profitability, and lower yield loss in the long run, relative to myopic management. Counterintuitively, myopic management leads to a lower resistance level through its higher robot adoption intensity. We also find that a lower level of initial weed seed resistance and/or a higher fitness cost result in a higher level of resistance because they create incentives for farmers to delay the adoption of robotic weed control. Our analysis shows the importance of jointly considering the interactions between weed ecology and economics in analyzing the incentives and effects of robotic weed management on weed resistance.

agricultural robotics↗
NASA NTRS2006

IMU/GPS System Provides Position and Attitude Data

A special navigation system is being developed to provide high-quality information on the position and attitude of a moving platform (an aircraft or spacecraft), for use in pointing and stabilization of a hyperspectral remote-sensing system carried aboard the platform. The system also serves to enable synchronization and interpretation of readouts of all onboard sensors. The heart of the system is a commercially available unit, small enough to be held in one hand, that contains an integral combination of an inertial measurement unit (IMU) of the microelectromechanical systems (MEMS) type, Global Positioning System (GPS) receivers, a differential GPS subsystem, and ancillary data-processing subsystems. The system utilizes GPS carrier-phase measurements to generate time data plus highly accurate and continuous data on the position, attitude, rotation, and acceleration of the platform. Relative to prior navigation systems based on IMU and GPS subsystems, this system is smaller, is less expensive, and performs better. Optionally, the system can easily be connected to a laptop computer for demonstration and evaluation. In addition to airborne and spaceborne remote-sensing applications, there are numerous potential terrestrial sensing, measurement, and navigation applications in diverse endeavors that include forestry, environmental monitoring, agriculture, mining, and robotics.

Lin, Ching Fang↗
NASA NTRS2018

Investigating Microbiome Differences Between Red Romaine Lettuce Grown from Sanitized and Unsanitized Seeds

The International Space Station (ISS) as an integral component for the discovery and development of advanced robotics, materials, communications, medicine, agriculture, and environmental science due to it currently being the world's only microgravity laboratory of its kind. Because the ISS is a contained system with confined quarters, much research has been undertaken to assess and diminish the number of microbiological risks associated with astronauts inhabiting the station for extended periods of time. Notable microbiological risk factors include drinking water, air, and food. As an avenue for both mental/emotional respite and a source of fresh produce for astronauts, a vegetable production system has been employed on the ISS. In order to understand the microbial risks involved with a "pick and eat" vegetable system on the International Space Station (ISS), this study aims to compare microbial differences between sanitized and unsanitized seeds by tracking and identifying seedborne microbes throughout the development of red romaine lettuce (Lactuca sativa)-a plant species that has already been grown on the ISS.

Polanco, Jonilee A.↗
NASA NTRS2016

Agriculture on Mars: Soils for Plant Growth

Robotic rovers and landers have enabled the mineralogical, chemical, and physical characterization of loose, unconsolidated materials on the surface of Mars. Planetary scientists refer to the regolith material as "soil." NASA is currently planning to send humans to Mars in the mid 2030s. Early missions may rely on the use of onsite resources to enable exploration and self-sufficient outposts on Mars. The martian "soil" and surface environment contain all essential plant growth elements. The study of martian surface materials and how they might react as agricultural soils opens a new frontier for researchers in the soil science community. Other potential applications for surface "soils" include (i) sources for extraction of essential plant-growth nutrients, (ii) sources of O2, H2, CO2, and H2O, (iii) substrates for microbial populations in the degradation of wastes, and (iv) shielding materials surrounding outpost structures to protect humans, plants, and microorganisms from radiation. There are many challenges that will have to be addressed by soil scientists prior to human exploration over the next two decades.

Ming, D. W.↗
DOE OSTI2021

Sensing Technology Survey for Obstacle Detection in Vegetation

This study reviews obstacle detection technologies in vegetation for autonomous vehicles or robots. Autonomous vehicles used in agriculture and as lawn mowers face many environmental obstacles that are difficult to recognize for the vehicle sensor. This review provides information on choosing appropriate sensors to detect obstacles through vegetation, based on experiments carried out in different agricultural fields. The experimental setup from the literature consists of sensors placed in front of obstacles, including a thermal camera; red, green, blue (RGB) camera; 360° camera; light detection and ranging (LiDAR); and radar. These sensors were used either in combination or single-handedly on agricultural vehicles to detect objects hidden inside the agricultural field. The thermal camera successfully detected hidden objects, such as barrels, human mannequins, and humans, as did LiDAR in one experiment. The RGB camera and stereo camera were less efficient at detecting hidden objects compared with protruding objects. Radar detects hidden objects easily but lacks resolution. Hyperspectral sensing systems can identify and classify objects, but they consume a lot of storage. To obtain clearer and more robust data of hidden objects in vegetation and extreme weather conditions, further experiments should be performed for various climatic conditions combining active and passive sensors.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2003

Hopping Robot with Wheels

A small prototype mobile robot is capable of (1) hopping to move rapidly or avoid obstacles and then (2) moving relatively slowly and precisely on the ground by use of wheels in the manner of previously reported exploratory robots of the "rover" type. This robot is a descendant of a more primitive hopping robot described in "Minimally Actuated Hopping Robot" (NPO- 20911), NASA Tech Briefs, Vol. 26, No. 11 (November 2002), page 50. There are many potential applications for robots with hopping and wheeled-locomotion (roving) capabilities in diverse fields of endeavor, including agriculture, search-and-rescue operations, general military operations, removal or safe detonation of land mines, inspection, law enforcement, and scientific exploration on Earth and remote planets. The combination of hopping and roving enables this robot to move rapidly over very rugged terrain, to overcome obstacles several times its height, and then to position itself precisely next to a desired target. Before a long hop, the robot aims itself in the desired hopping azimuth and at a desired takeoff angle above horizontal. The robot approaches the target through a series of hops and short driving operations utilizing the steering wheels for precise positioning.

Barlow, Edward↗
NASA NTRS1988

Space Station Workshop: Commercial Missions and User Requirements

The topics of discussion addressed during a three day workshop on commercial application in space are presented. Approximately half of the program was directed towards an overview and orientation to the Space Station Project; the technical attributes of space; and present and future potential commercial opportunities. The remaining time was spent addressing technological issues presented by previously-formed industry working groups, who attempted to identify the technology needs, problems or issues faced and/or anticipated by the following industries: extraction (mining, agriculture, petroleum, fishing, etc.); fabrication (manufacturing, automotive, aircraft, chemical, pharmaceutical and electronics); and services (communications, transportation and retail robotics). After the industry groups presented their technology issues, the workshop divided into smaller discussion groups composed of: space experts from NASA; academia; industry experts in the appropriate disciplines; and other workshop participants. The needs identified by the industry working groups, space station technical requirements, proposed commercial ventures and other issues related to space commercialization were discussed. The material summarized and reported are the consensus from the discussion groups.

Source record↗
NASA NTRS2002

Why, from a Life Sciences Perspective, This Mission to Mars?

Mars may have had water and life early in its history and this make it a key target for robotic and human exploration. Extensive human exploration of Mars will of necessity depend on life support systems that rely on agricultural plants. If current concept for recreating, a biosphere on Mars are implemented this would involve widespread use of plants, particularly species from Arctic and alpine environments.

McKay, Christopher P.↗
DOE OSTI2023

Apparatus and method for agricultural data collection and agricultural operations

Aspects of the subject disclosure may include, for example, obtaining video data from a single monocular camera, wherein the video data comprises a plurality of frames, wherein the camera is attached to a mobile robot that is travelling along a lane defined by a row of crops, wherein the row of crops comprises a first plant stem, and wherein the plurality of frames include a depiction of the first plant stem; obtaining robot velocity data from encoder(s), wherein the encoder(s) are attached to the robot; performing foreground extraction on each of the plurality of frames of the video data, wherein the foreground extraction results in a plurality of foreground images; and determining, based upon the plurality of foreground images and based upon the robot velocity data, an estimated width of the first plant stem. Additional embodiments are disclosed.

Chowdhary, Girish↗
NASA NTRSDate not supplied

Lunar In-situ Resource Utilization Concept to Reality

ISRU is a capability involving multiple elements to achieve final products (mobility, product storage and delivery, power, crew and/or robotic maintenance, etc.) ‘ISRU’ does not exist on its own. By definition, it must connect and tie to users/customers of ISRU products and services Living Off the Land: ISRU involves any hardware or operation that harnesses and utilizes ‘in-situ’ (local) resources to create products and services for robotic and human exploration. Resource Examples •Water •Oxygen •Hydrogen •Carbon •Metals •Silicon •Nitrogen •Regolith/Rock •Discarded materials Product Examples •Propellant •Life Support Consumables •Feed stock for •Additive manufacturing •Construction •Agriculture substrate and/or fertilizer

lunar↗
DOE OSTI2025

xGFabric: Coupling Sensor Networks and HPC Facilities with Private 5G Wireless Networks for Real-Time Digital Agriculture

Advanced scientific applications require coupling distributed sensor networks with centralized high-performance computing facilities. Citrus Under Protective Screening (CUPS) exemplifies this need in digital agriculture, where citrus research facilities are instrumented with numerous sensors monitoring environmental conditions and detecting protective screening damage. CUPS demands access to computational fluid dynamics codes for modeling environmental conditions and guiding real-time interventions like water application or robotic repairs. These computing domains have contrasting properties: sensor networks provide low-performance, limited-capacity, unreliable data access, while high-performance facilities offer enormous computing power through high-latency batch processing. Private 5G networks present novel capabilities addressing this challenge by providing low latency, high throughput, and reliability necessary for near-real-time coupling of edge sensor networks with HPC simulations. This work presents xGFabric, an end-to-end system coupling sensor networks with HPC facilities through Private 5G networks. The prototype connects remote sensors via 5G network slicing to HPC systems, enabling real-time digital agriculture simulation.

Digital Agriculture↗