AGRO NAVÓ Plan – Software for planning and evaluation of the path and work of field robots

Hans Glasmacher

ABSTRACT

There are several reasons for a detailed planning of the driving route and the implement tasks for partially or totally autonomous field robots, especially when high accuracy or complex jobs are demanded, or new robot-like tractors (e.g. without a driver seat or steering wheel) will be developed. But also the reduction of necessary machine working time in the field by an optimal preparation in the office is a goal, especially when repeatedly used for time critical work.

The planning software AGRO NAV Plan starts with surveyed field boundaries and obstacle polygons. After selection of a vehicle and implements the user continues with the definition of treatment zones, working direction, driving strategy, turn lands, velocities, and so on. Manual or semi-automatic path and implement control generation are possible. During the planning process collision control and implement compatibility tests are executed.

All data are stored in a database with functions to export Jobs to PC-Card, import completed work data from a PC-Card, as well as data exchange functions to other manufacturers software.

The flexibility of the software allows even jobs with very special challenges to be planned and completed by machines equipped with the AGRO NAV system for autonomous vehicle and implement steering. Examples are presented.

 

KEYWORDS. Automatic steering, Autonomous working, Agriculture, Collision control, Computer software, Electronics, Erosion control, Field Surveying, GIS, GPS, guidance, Implement steering, Implement control, Monitoring, Navigation, Kalman filter, Off-road vehicles, Parallel Swathing, Planning, Precision farming, Radar, Robots, Route planning, RTK-GPS, Site specific, Three dimensional, Topography, Tracking, Tractors, tramlining, Weed control, Working pattern.

Introduction

AGRO NAV is a precision navigation and control system for agricultural vehicles and implements. To realize this accuracy and with respect to the future of robots without manual steering, additionally a sophisticated planning software for agricultural tasks was developed. This presentation will explain the functionality and emphasize the benefits of this software, called AGRO NAV Plan.

Software for planning and evaluation of path and work of field robots

 

Description of the complete AGRO NAV system

AGRO NAV is a self-contained high precision vehicle-based navigation and control system, consisting of several elements inside and outside of the vehicle. The first visible is the AGRO NAV Navigation Computer GT 2000, which runs the User Interface and the complete navigation software package, and is in principle a ruggedised Pentium PC. The navigation hardware components are a RTK-GPS receiver with UHF data radio, fibre gyro, tilt sensors, and a radar speed sensor. The vehicle has to be prepared for steering, speed and hydraulic system control by wire to communicate with the navigation software. In general, this is realized via a CAN bus by a job controller, to interface the signals between the main Navigation Computer and the vehicle’s electronic and hydraulic systems, together with vehicle specific software (Freimann 2000/2).

The real-time navigation software AGRO NAV Drive consists of the components: Man Machine Interface with the process control module, the navigation software with an integrated Kalman filter, the steering module and implement control module. The software supports user functions such as surveying new fields for the job planning process, learning a job by doing, selecting a prepared job out of a set for execution, guiding the driver to the starting or interruption point, and visualization and control during the job.

AGRO NAV is designed for high accuracy demands. Though the accuracy is partly dependent on the sensors and actuators of the vehicle, it is in general better than +/- 10 cm. At low speed on flat ground about +/- 2-3 cm are typical, and the repeat accuracy is even better (Freimann 2000/1).

One difference of AGRO NAV to all other known approaches to automatic driving of vehicles is the complete and detailed pre planning of the work to be done. The explanation of the planning process and of its advantages will be the main subject of this manuscript. To clarify this process, the sequential steps to complete one planning pass will be described.

 

Advantages and Disadvantages of Job Planning

To start with, the advantages and disadvantages will be presented, as GEO TEC is the only company to use planning. I will only state the arguments, not discuss, rate and assess them.

The main disadvantage is, that some work at the PC must be done before going to the field. The other disadvantages:

·       Software learning curve.

·       The flexibility is limited when new obstructions or restrictions have to be taken into account, and for ad hoc decisions and modifications of jobs.

To compensate this there are several advantages in preparing the field work in detail in advance. The possible advantages of pre-planning jobs:

·       No delays in field operations as a result of confusing or unclear instructions.

·       Work with zero overlap or equally distribute the inevitable double work across all rows.

·       Work under low visibility conditions.

·       Avoid damage by hidden obstacles.

·       Minimize soil compaction by precise definition of traffic lanes or tracks with respect to the field borders.

·       Optimise the driving pattern with respect to corresponding working widths, restrictions imposed by different implements, the form factor and width of fields, topography, soil, etc.

·       Paths and work can be repeated with the same accuracy.

·       Planning can be done out of season thus saving time during the cropping season.

·       New working methods can be implemented, e.g. new drive patterns with skipped loops.

·       Programming of totally autonomous vehicles.

 

Description of the planning process

The job planning process is based on three major information sources: the field, the vehicle and the implements. The characteristics of the last two are fixed but field data must be determined by the farmer himself.

Initially, the farmer surveys his fields with AGRO NAV Drive using the survey mode. He selects the desired survey point of the vehicle, for example the left front wheel, and then drives around the field. If the field has straight borders, he may choose to mark only the edges exactly, otherwise he may drive the boundary as accurately as possible. If there are obstacles inside or near the field, either below and/or above the ground, they can be surveyed and categorised by corresponding marker types. The pictures show screen-shots of a simple field survey and another one with obstacles.

 

The data is stored on a PC-Card and is later read by the AGRO NAV Plan software, where the data are visualized. The user can now determine graphically and by the use of rubber band lines, which corners are fixed, which lines are straight, and where to set curves to use the land optimally, and thereby reveal errors made during surveying. The results are closed polygons describing the field and all obstacles. For a better perception on the screen, a bitmap of an aerial photo or a scan of a map can be displayed and adjusted as a screen background. These data are then saved along with additional data in the database and form the prerequisites for the design of the future jobs.

After the selection of a field the planning process in AGRO NAV Plan assists with the parameterisation of the planned job by permitting a vehicle and implement combination to be either selected or defined using the available list of hardware drivers. The drivers contain all necessary information about velocities, dynamics, dimensions and functional range. The user can then determine the variable data, e.g. speed and implement functions. The screen shot shows the selection of seeding equipment.

Parallel help lines for the tracks can be generated easily from the field polygon as a framework for the driving pattern. Some examples are shown in the following screen shots:

 

 

Based on this framework the user continues by defining treatment zones and working direction, the definition of the turn lands, driving strategy and pattern, and so on. Manual or semi-automatic path and implement control generation are possible. During the planning process, the job is analysed in detail, including collision control with obstacles as well as compatibility tests of the implement functions. The final result is a complete and detailed program for AGRO NAV Drive to execute.

This program represents not only the path, but the complete work, including for example very accurate lower and raise points of an implement as well as the headland turns. It can be repeated as often as desired, and can, of course, be repeatedly modified and edited by AGRO NAV Plan. All data are stored in a database with functions to export Jobs to a PC-Card, import completed work data from a PC-Card, as well as planned data exchange functions to other commercial software.

When initiating a job in the field, the prepared data is selected and loaded from the PC-Card into AGRO NAV Drive. The driver is guided to the starting point of the planned job and, when he has arrived, obtains permission to start the Job. If legally permitted, he can also leave the vehicle, start it with a remote control device and observe the work from a distance.

 

Examples of planned Jobs

The following examples were executed by machines equipped with our AGRO NAV system for autonomous vehicle steering and implement control. The software is flexible enough to handle very special challenges like these jobs, namely:

a) Setting asparagus


In this specific case of yearly asparagus field preparation it is important to heap the dams centrally above the plant rows, as shown below. This implies that the positions of the plant rows can be exactly determined. In the best case, the positions are recorded during setting, otherwise they can be surveyed afterwards using AGRO NAV Drive.

 


Additionally, in the presented example, the slope of the field had to be considered because the parallel dams will dam up the rain water without a steady gradient, and this will influence the temperature of the plants and later the crop yield. On the basis of the survey data the optimal row direction was evaluated and the gradients checked by calculation of elevation profiles.

Because asparagus is very demanding concerning soil quality, part of the field with lower soil quality was surveyed and excluded from planting.

The picture shows a perspective view of the terrain and the resulting job planning.

     

 

The planned path was a mixture of loop work, as shown on the work progress display of the Navigation computer. In the middle of the field, a group of rows with turnabouts was planned, because a different kind of asparagus was to be planted in the northern part. The planting process is shown below.

 

As the tractor had to drive very slowly, at about 0.5 meter per second, it took 2 days to plant about 30 000 square meters.

In the following years, the same asparagus planning framework will be used to heap the dams centrally above the plant rows or to level the dams in autumn.


b) Plant breeding

For scientific field experiments the accurate documentation of the whole vegetation period is of importance. The base is laid out by the so called experimental design, which defines the patterns of the parcels and the streets in between, the number of rows, the number and length of parcels, as well as the different treatments of each parcel.


 

 


Especially for seeding on a unstructured and bare field AGRO NAV is extremely helpful, as no stake out work is necessary in advance to mark up the rows and parcels, and the rows can be made straighter then is possible manually. Additionally, only one man is needed to feed the sowing machine with the different kinds, no additional driver is necessary in the field, and you can see on the photograph that the driver’s seat is unoccupied.


 


In this case not only a small lateral error for the rows is desirable, but also the longitudinal accuracy for starting and stopping the seeding machine is of importance. 


 

 


Conclusion

To achieve high geometrical accuracy of specific agricultural field tasks, e.g. mechanical weed control, programming of autonomous robots, preplanning of the drive path is necessary. The software tool AGRO NAV Plan has proven to be useful for programming the drive path and implement steering for demonstrations as well as for actual field work. Many new possibilities exist to reduce work and cost in the field by preplanning jobs at the PC. The aim will therefore be to simplify the planning process without losing the flexibility to plan even special tasks.

References

1.       Sterlemann, F.: AGRO NAV Autonomous Off-road Vehicle Navigation and Implement Control System, using CDGPS and Inertial Backup. AgEng 2000, Proc. Int. Conf. on Agricultural Engineering, Warwick, 02./07.07.2000. Paper 00-IE-007ii. H.1

2.       Freimann, R.: Investigation of Position Accuracy of an Autonomous Offroad Vehicle Navigation. AgEng 2000, Proc. Int. Conf. on Agricultural Engineering, Warwick, 02./07.07.2000. Paper 00-IE-007ii. H.1

3.       Freimann, R.: Autonavigation and Implement Controlled Process Automation on CAN. Proc. Int. Symposium on Electronic Farm Communication with LBS. Nov. 20, 2000, Hokkaido University, Sapporo. S.64/87

4.       Wit J. S. : Vector pursuit path tracking for autonomous ground vehicles, Dissertation at the University of Florida, August 2000

5.       Simon, A and Becker, J. C. : Vehicle Guidance for an Autonomous Vehicle, IEEE International Conference of intelligent Transportation Systems, 1999

6.       Simon, A and Becker, J. C. et al. : A Decentralized Path Planning and Control Structure for an autonomous Vehicle, International Conference on intelligent Vehicles, 1998