Autonomous Robots 13, 5–7, 2002c© 2002 Kluwer Academic Publishers. Manufactured in The Netherlands.

Guest Editorial: Agricultural Robotics

ALBERT-JAN BAERVELDTIntelligent Systems Lab, School of Information Science, Computer and Electrical Engineering,

Halmstad University, Halmstad, Swedenalbert@ide.hh.se

Welcome to the special issue of the journal Au-tonomous Robots on the promising area of AgriculturalRobotics!

The call for papers for this special issue was dis-tributed in the beginning of 2001 to a significant num-ber of research groups belonging to the robotics re-search community or to the agricultural engineeringresearch community. Three reviewers for each paperwere selected in such a way that both communitieswere represented. This is the type of exchange I wouldlike to encourage, in order to promote closer contactand cooperation between the two communities. Thesolicitation of survey articles was omitted for this spe-cial issue, as the Journal of Computers and Electronicsin Agriculture published a special issue on Navigat-ing of Agricultural Field Machinery edited by GerhardJahns, Volume 25 (2000) 1–2, containing several sur-vey articles. The reader is referred to that special issuefor survey articles. Finally, seven papers were selectedfor this special issue, covering most recent advances inthe area of agricultural robotics.

The first paper of this issue “The Demeter Systemfor Automated Harvesting”, by Pilarski, Happold, Pan-gels, Ollis, Fitzpatrick and Stentz presents a roboticharvesting machine. The machine uses video cameras,GPS, and dead reckoning to navigate and cut crop. Thereaders of this journal are already familiar with the sys-tem as it appeared as an illustration on the front coverof Volume 8. Demeter is capable of planning harvest-ing operations for an entire field, and then executingits plan by cutting crop rows, turning to cut successiverows and detecting unexpected obstacles. The systemhas cut hundreds of acres fully autonomously in a vari-ety of fields. The success of the Demeter project, whichuses two complementary guidance systems made ofcomponents available off-the-shelf, demonstrates that

commercially viable automated harvesting is attainablein the near future.

The second paper “An Agricultural Mobile Robotwith Vision-Based Perception for Mechanical WeedControl” by Astrand and Baerveldt, presents an agri-cultural mobile robot for mechanical weed control. Thegoal is to replace the use of chemicals for weed controlby mechanical weed control, a necessity for so-calledorganic farming. There is political interest in the Eu-ropean Union to increase the amount of organicallygrown products. The goal is that about 5 to 10% of thetotal field area should be processed by organic farmingmethods by the year 2005. Organic farming is not onlya political goal; there is also a push from the market.More and more environmental conscious customers areasking for products that are organically grown. Therobot, presented in the paper, employs two vision sys-tems. One gray-level vision system that is able to recog-nize the row structure formed by the crops and to guidethe robot along the rows and a second, color-based vi-sion system that is able to identify a single crop amongweed plants. This vision system controls a weeding-tool that removes the weed within the row of crops.

The third paper “Online Learning and Adaptation ofAutonomous Mobile Robots for Sustainable Agricul-ture”, by Hagras, Colley, Callaghan, and Carr-West,presents the application of their hierarchical fuzzy-genetic system to produce an autonomous outdooragricultural mobile robot capable of learning andadaptation. In the agricultural setting, a high degreeof variation is present from many perspectives: e.g.,from plant to plant, from field to field, from day to daywith respect to weather conditions and growth of veg-etation, and from one year to the other. To be able tocope with this, robots capable of learning and adapta-tion are needed. The paper presents a system concerned

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with producing an intelligent mobile robot that learnsthe basic behaviors needed for navigation in outdooragricultural environments and their coordination to per-form complex tasks. The robot can adapt to differentenvironmental and ground conditions without humanintervention in a short time interval and it implementsa life long learning strategy and can navigate continu-ously for long periods.

The fourth paper “Automatic Guidance of a FarmTractor Relying on a Single CP-DGPS” by Thuilot,Cariou, Martinet, and Berducat, presents a method de-scribing how a tractor can follow pre-defined curvedpaths very accurately relying on a single CP-DGPS.State-of-the-art Carrier Phase Differential GPS (CP-DGPS), also denoted as Real-Time Kinematic GPSreaches the centimeter accuracy at update rates around1 second or less. This clearly allows the design and theimplementation of an absolute vehicle guidance sys-tem. A few years ago, the first commercial guidancesystems relying on a CP-DGPS dedicated to agricul-tural use, were introduced on the market. The objectiveof this paper is to investigate the possibility to achieveaccurate curved path following based on a single CP-DGPS. The vehicle heading is derived according toa Kalman state reconstructor and a nonlinear veloc-ity independent control law is designed. Field experi-ments with a full-sized farm tractor, demonstrating thecapabilities of the guidance system, are reported anddiscussed.

The fifth paper “Relating Torque and Slip in an Odo-metric Model for an Autonomous Agricultural Vehi-cle”, by Lindgren, Hague, Probert Smith and Marchant,presents a new odometric model based on torque mea-surements. GPS and machine vision are emerging as themost promising sensors for guidance of autonomousoutdoor vehicles, GPS for general position within afield, and machine vision for example for fine posi-tioning relative to crop rows. However, odometers arestill probably the most widely used navigation sensors.They are often part of a position estimation systembased on GPS, where sensor fusion is achieved througha Kalman filter. Compared to indoor mobile robotics,outdoor agricultural robots meet different kind of soilsurfaces resulting in varying soil deformations and thewheels may have slightly varying diameters due to ac-cumulation of dirt and due to air pressure variations.Moreover, the wheels slip due to traction as maxi-mum traction occurs at non-zero values of slip, whichis more likely to occur in agricultural settings. Theodometric model, presented in this paper, relates mea-

surements of torque applied to the wheels with wheelslip.

The sixth paper “A System for Semi-AutonomousTractor Operations” by Stentz, Dima, Wellington,Herman and Stager, presents a system for semi-autonomous tractor operations. Although full auton-omy is the ultimate goal for robotics, it may be along time coming. High demands on safety and ro-bustness are difficult to achieve, while aiming at fullautonomy, especially in outdoor agricultural environ-ments. However, partial autonomy can add value to amachine long before full autonomy is achieved. Suchsemi-autonomous machines optimize the capabilitiesof both machines and humans as intelligent and coop-erative entities. The machine, in this case a tractor, isdesigned to do the most of the laborious and repetitivework and a human operator acts remotely as a supervi-sor and teacher, and handles exceptions. The intentionis that one operator supervises several tractors. Thecomplete system was tested in a Florida orange grove,where it drove several kilometers.

The seventh and last paper “An Autonomous Robotfor Automated Harvesting Cucumbers in Green-houses” by van Henten, Hemming, van Tuijl, Kornet,Meuleman, Bontsema, and van Os, presents a robot forharvesting cucumbers in an indoor environment. Man-ual labor in a greenhouse is demanding, especially un-der poor climatic conditions, and the earnings are low.Therefore, it is becoming more and more difficult toobtain adequate staff, which motivates research on asuitable automation. The robot presented in this paperemploys two vision systems. One system is mountedon the vehicle and is used for the detection of the fruit,determination of the ripeness and quality of the fruitas well the 3D-localisation of the fruit for robot mo-tion planning. The other camera is mounted on the topof the end-effector and is used for stereo imaging inthe neighborhood of the cucumber during the final ap-proach with the gripper. Field tests confirmed the abilityof the robot to pick cucumbers with a success rate of80% and at an average rate of 45 seconds. Please notethat this paper will appear in the next regular issue ofthe journal Autonomous Robots, as all the seven papersdid not fit in one issue.

The special issue shows that in the future we can ex-pect to see robot systems for several harvesting opera-tions. We can also expect to see robots performing otherkinds of agricultural operations autonomously such asspraying and mechanical weed control, guided primar-ily by GPS and machine vision but also by other sensor

Guest Editorial 7

systems. Such robotic systems would mean a revolutionfor farming allowing farmers to treat individual plantsor trees in a field. It will be very interesting to followthe developments in the area of agricultural robotics:will for example the tractor remain the versatile agri-cultural machine as it is today or will the fields in thefuture also be populated with smaller, more specialized,mobile robots?

During the editorial work of this special issue, a webpage has been compiled which contains links to a sig-nificant number of research groups in the area of agri-cultural robotics, as well as to a number of companiesproviding GPS and machine vision systems dedicatedto agricultural applications. The web page can be foundat:

• http://www.hh.se/staff/albert/agrorobotics.html

Finally, I would like to thank the reviewers for theirclose cooperation and all the authors for their valuablecontributions to this issue. I also want to express mygratitude to the editor, Professor George A. Bekey, forinitiating and encouraging this special issue.

Albert-Jan Baerveldt is a Professor of Mechatronic Systems at theSchool of Information Science, Computer and Electrical Engineeringat Halmstad University in Sweden, where he holds the Getinge Chairof Mechatronic Systems. He received the Ph.D. degree in Mechatron-ics from the Swiss Federal Institute of Technology, Zurich in 1993,where he conducted research mainly in the field of vision-guidedrobot arms. During this time he also won the first worldchampi-onship for ping pong playing robots in Hong-Kong in 1992. HisPh.D. work on the bin-picking problem was awarded with a grantto exhibit the work at the “Research and Development Exhibition”at the Hannover Fair 1992 in Germany, which is one of the largestindustrial fairs in the world. In 1994 he had a postdoc position at theInstitute of Automatic Control at Lund Technical University, Lundin Sweden. Since 1994 he has been working at Halmstad Universityin Sweden. Currently he is leader of the Intelligent Systems Lab. Hisresearch interest include robotics and computer vision.