CROPS : high tech agricultural robots

In the EU-funded CROPS (Clever Robots for Crops) project high tech robots are developed for site-specific spraying and selective harvesting of fruit and fruit vegetables. The harvesting robots are being designed to harvest high-value crops such as greenhouse vegetables, fruits in orchards and grapes for premium wines. The CROPS robots are also developed for canopy spraying in orchards and for precision target spraying in grape vines to reduce the use of pesticides. A CROPS robot will be able to detect the fruit, sense its ripeness, then move to grasp and gently detach only the ripe fruit. For crop protection the canopy sprayer can detect contours of trees in an orchard and consequently only spraying on the trees and the precision target sprayer can detect diseases on leaves of vine grapes and only spray pesticides on the affected spots of the leaves. In the CROPS project also attention is paid to reliable detection and classification of objects and obstacles for autonomous navigation in a safe way in plantations and forests. For the several applications within the CROPS project platforms were developed. Sensing systems and appropriate vision algorithms for the platforms have been developed. For the software platform the Robot Operating System (ROS) is used. A 9 degrees of freedom (DOF) manipulator was designed and built and tested for sweet-pepper harvesting, apple harvesting and in close range spraying. The 9-DOF manipulator is modular, since the joint configuration can be adapted to the applications, e.g. 6 DOF for the close range spraying. For the different applications different end-effectors were designed and tested. The main results of the CROPS project will be the applications, the so-called demonstrators For sweet pepper a platform that can move in between the crop rows on the common greenhouse rail system which also serves as heating pipes was built and equipped with a sensing and lightning system, the manipulator and end-effectors. The complete system was tested and showed to growers in a lab situation. The apple harvesting platform is based on a current mechanical grape harvester. In discussion with growers so-called 'walls of fruit trees' have been designed which bring robots closer to the practice. This system, equipped with a sensing system the CROPS manipulator and a special end-effector, has been successfully tested in an orchard. A canopy-optimised sprayer has been designed as a trailed sprayer with a centrifugal blower. The system has been successfully tested in an orchard with a significant reduction of pesticide use. For close range target spraying the spraying robot in a greenhouse experiment with grape vines reduced the pesticide consumption with 84%

Urban-Tree-Attribute Update Using Multisource Single-Tree Inventory

Peer reviewe

Multisource Single-Tree Inventory in the Prediction of Tree Quality Variables and Logging Recoveries

Peer reviewe

Estimating the Position of the Harvester Head – a Key Step towards the Precision Forestry of the Future?

Modern harvesters are technologically sophisticated, with many useful features such as the ability to automatically measure stem diameters and lengths. This information is processed in real time to support value optimization when cutting stems into logs. It can also be transferred from the harvesters to centralized systems and used for wood supply management. Such information management systems have been available since the 1990s in Sweden and Finland, and are constantly being upgraded. However, data on the position of the harvester head relative to the machine are generally not recorded during harvesting. The routine acquisition and analysis of such data could offer several opportunities to improve forestry operations and related processes in the future. Here, we analyze the possible benefits of having this information, as well as the steps required to collect and process it. The benefits and drawbacks of different sensing technologies are discussed in terms of potential applications, accuracy and cost. We also present the results of preliminary testing using two of the proposed methods. Our analysis indicates that an improved scope for mapping and controlling machine movement is the main benefit that is directly related to the conduct of forestry operations. In addition, there are important indirect benefits relating to ecological mapping. Our analysis suggests that both of these benefits can be realized by measuring the angles of crane joints or the locations of crane segments and using the resulting information to compute the head\u27s position. In keeping with our findings, two companies have recently introduced sensor equipped crane solutions

Enhanced Algorithms for Estimating Tree Trunk Diameter Using 2D Laser Scanner

Accurate vehicle localization in forest environments is still an unresolved problem. Global navigation satellite systems (GNSS) have well known limitations in dense forest, and have to be combined with for instance laser based SLAM algorithms to provide satisfying accuracy. Such algorithms typically require accurate detection of trees, and estimation of tree center locations in laser data. Both these operations depend on accurate estimations of tree trunk diameter. Diameter estimations are important also for several other forestry automation and remote sensing applications. This paper evaluates several existing algorithms for diameter estimation using 2D laser scanner data. Enhanced algorithms, compensating for beam width and using multiple scans, were also developed and evaluated. The best existing algorithms overestimated tree trunk diameter by ca. 40%. Our enhanced algorithms, compensating for laser beam width, reduced this error to less than 12%

Predicting vegetation characteristics in a changing environment by means of laser scanning

Accurate and up-to-date information concerning vegetation characteristics is needed for decision-making from individual-tree-level management activities to the strategic planning of forest resources. Outdated information may lead to unbeneficial or even wrong decisions, at least when it comes to the timing of management activities. Airborne laser scanning (ALS) has so far been successfully used for applications involving detailed vegetation mapping because of its capability to simultaneously produce accurate information on vegetation and ground surfaces. The aim of this dissertation was to develop methods for characterizing vegetation and its changes in varying environments. A method called multisource single-tree inventory (MS-STI) was developed in substudy I to update urban tree attributes. In MS-STI stem map was produced with terrestrial laser scanning (TLS) and by combining the stem map with predictors derived from ALS data it was possible to obtain improved estimates of diameter-at-breast height but also to produce new attributes such as height and crown size. Boat-based mobile laser scanning (MLS) data were employed in substudy II to map riverbank vegetation and identify changes. The overall classification accuracy of 73% was obtained, which is similar to accuracies found in other studies. With multi-temporal MLS data sets changes in vegetation were mapped year to year. In substudy III, open access ALS data were combined with multisource national forest inventory (NFI) data to investigate the drivers associated to wind damage. The special interest was in ALS-based predictors to map areas with wind disturbance and apply logistic regression to produce a continuous probability surface of wind predisposition to identify areas most likely to experience wind damage. The results demonstrated that a combination of ALS and multisource NFI in the modelling approach increased the prediction accuracy from 76% to 81%. The dissertation showed the capability of ALS and MLS for characterizing vegetation and mapping changes in varying environments. The developed applications could increase and expand the utilization of multi-temporal 3D data sets as well as increase data value. The results of this dissertation can be utilized in producing more accurate, diverse, and up-to-date information for decision-making related to natural resources.Luonnonvaroja koskevaa päätöksentekoa varten tarvitaan luotettavaa ja ajantasaista tietoa, oli kyse sitten yksittäiseen puuhun liittyvistä toimenpiteistä tai laajojen alueiden strategisesta suunnittelusta. Vanhentunut tieto voi johtaa epäedullisiin tai jopa vääriin ratkaisuihin, erityisesti hoitotoimenpiteiden ajoituksen osalta. Ilmalaserkeilaus on menetelmä, jossa yksityiskohtaista kolmiulotteista tietoa tuotetaan esimerkiksi lentokoneeseen tai helikopteriin asennetun laserkeilaimen avulla. Laserkeilan mittaa etäisyyttä kohteeseen laserpulssin kulkuajan perusteella. Ilmalaserkeilaus on jo operatiivisessa käytössä metsävaratiedonkeruussa Pohjoismaissa sillä sen avulla voidaan tuottaa tarkkaa tietoa samanaikaisesti sekä maanpinnan korkeudesta ja maaston muodoista että kasvillisuuden pituudesta ja tiheydestä. Maastolaserkeilauksella tarkoitetaan pienemmän alueen inventointiin soveltuvaa menetelmää, jossa laserkeilain on kolmijalan päällä tai liikkuvalla alustalla. Väitöskirjan tavoitteena oli kehittää menetelmiä kasvillisuuden ominaisuuksien ennustamiseen laserkeilauksen avulla erilaisissa ympäristöissä. Väitöskirja koostuu kolmesta osajulkaisusta, joista ensimmäisessä kehitettiin monilähteinen yksittäisten puiden inventointimenetelmä kaupunkipuiden tunnusten päivittämiseen. Kyseisessä menetelmässä maastolaserkeilauksen avulla tuotettiin puukartta, joka yhdistettiin ilmalaserkeilauksella saatuihin tietoihin. Ilmalaserkeilauksesta saatujen yksittäisten puiden latvojen pituus- ja tiheystunnusten avulla voitiin parantaa kaupunkipuiden läpimittatietoja sekä tuottaa uusia tunnuksia kuten pituus ja latvuksen koko lisättäväksi kaupunkipuurekisterin tietokantaan. Toisessa osajulkaisussa käytettiin veneeseen asennettua laserkeilainta jokiympäristön kasvillisuuden kartoittamiseen sekä kasvillisuudessa tapahtuneiden muutosten havainnoimiseen. Kasvillisuus ja paljas maa oli mahdollista erotella 73 prosentin tarkkuudella, vastaaviin tarkkuuksiin on päästy myös aiemmissa tutkimuksissa, joissa tosin hyödynnettiin tarkempaa maastoaineistoa. Useampiaikaisilla aineistoilla oli mahdollista kartoittaa vuosien välillä tapahtuneita kasvillisuuden muutoksia. Kolmannessa osajulkaisussa hyödynnettiin avoimesti saatavilla olevaa ilmalaserkeilaus- ja monilähteistä valtion metsien inventoinnin (VMI) aineistoa tuulituhojen kartoittamiseen sekä ennustamiseen. Osajulkaisussa ennustettiin tuulituhoriskin suuruutta ilmalaserkeilauksesta saatavien maanpinnan korkeuden ja kasvillisuuden pituuden sekä monilähde-VMI-aineistosta saadun puulajitiedon avulla. Tarkoituksena oli selvittää tuhoriskille erityisen alttiit alueet mahdollisia metsänhoitotoimenpiteitä varten. Puulajitieto lisäsi tuulituhojen kartoitustarkkuutta 76 prosentista 81 prosenttiin. Väitöskirja esitteli erilaisilta alustoilta tehtävän laserkeilauksen kykyä kasvillisuuden luonnehtimiseen sekä muutosten huomioimiseen erilaisissa ympäristöissä monipuolista päätöksentekoa varten. Kaupunkiympäristöissä yksittäisten puiden tunnukset ovat kohdennettujen toimenpiteiden kannalta tärkeitä, kun taas tietoa jokiympäristöjen kasvillisuudesta ja sen muutoksista voidaan hyödyntää päivitettäessä tulvariskimalleja. Tieto tuulituhoille riskialttiista alueista voi auttaa metsänomistajia ja ammattilaisia metsänhoitotoimenpiteiden suunnittelussa. Väitöskirjassa kehitettyjen menetelmien avulla voidaan laajentaa useampiaikaisten laserkeilausaineistojen hyödyntämistä sekä saada lisäarvoa aineistoista. Väitöskirjan tuloksia voidaan hyödyntää tarkemman, monipuolisemman ja ajantasaisemman tiedon tuottamisessa erilaisessa luonnonvaroja koskevassa suunnittelussa ja päätöksenteossa