Open Access

This article proposes the concept of a simulation framework for environmental sensors with multilevel abstraction in agricultural scenarios. The implementation case study is a simulation of a grain-harvesting scenario enabled by LiDAR sensors. Environmental sensor models as well as kinematics and dynamic behavior of machines are based on the robotics simulator Gazebo. Models for powertrain, machine process aggregates and peripheral simulation components are implemented with the help of MATLAB/ Simulink and with the robotics middleware Robot Operating System (ROS). This article deals with the general concept of a multilevel simulation framework and in particular with sensor and environmental modeling.

Es werden drei Modellierungsansätze zur Simulation von Laserscannern in Pflanzenbeständen für die Entwicklung umfeldbasierter Fahrzeugfunktionen beschrieben. Das Sensorsignal der Distanzmessung wird dabei anhand realer Messwerte oder phänomenologisch und auf der Basis empirisch ermittelter Kennwerte in Abhängigkeit von objekt- und sensorspezifischen Einflussfaktoren abgebildet. Basierend auf den Methoden zur Simulation von Distanzmesssystemen der Open Source Simulationsumgebung Gazebo wurden die Modellierungsansätze als spezifische Sensor- und Umfeldmodelle implementiert. Die Modelle wurden insbesondere für den Einsatz an mobilen landwirtschaftlichen Arbeitsmaschinen und für die Anwendung in der Getreideernte optimiert.

Knowledge of the small-scale nutrient status of a field is an important basis for decision-making when it comes to optimising the fertiliser use in crop production. Currently, the traditional method involves soil sampling in the field and soil sample analysis in the laboratory as two separate working processes. The previous research project "soil2data" developed a mobile field laboratory for different carrier vehicles. In the follow-up project "prototypes4soil2data", the results of soil2data are further developed. A mixed soil sample is collected during the drive on the field. The soil sample is then wet-chemically prepared and analysed. The overall soil sampling and analysis process is divided into the following process steps: soil sampling planning, soil sampling, soil preparation, soil analysis and data management. The process steps are modified for the mobile field laboratory and the process steps run in parallel. The new soil extraction method is based on official German methods (VDLUFA) to ensure the interoperability of the analysis results with the VDLUFA fertiliser recommendations. An innovative key component is the NUTRISTAT analysis module (lab-on-chip with ISFET measurement technology). It can measure pH, the nutrients NO3-, H2PO4-, K+ and the electrical conductivity. In addition to the advantages of rapid data availability and no need to transport soil material to the laboratory, it provides a future basis for new application, e.g. verification of current results in the field during soil sampling with existing results or dynamic adjustment of soil sampling during work in the field.

Knowledge of the small-scale nutrient status of arable land is an important basis for optimizing fertilizer use in crop production. A mobile field laboratory opens up the possibility of carrying out soil sampling and nutrient analysis directly on the field. In addition to the benefits of fast data availability and the avoidance of soil material transport to the laboratory, it provides a future foundation for advanced application options, e.g. a high sampling density, sampling of small sub-fields or dynamic adaptation of the sampling line during field sampling. An innovative key component is the NUTRI-STAT ISFET sensor module. It measures values for the ions "NO3- ”, “H2PO4- " and "K+ " as well as the pH. The ISFET sensor module was specially developed for soil nutrient analysis. The phosphorus measurement was further developed for the project "soil2data". First results from the ISFET sensor module show a measurement signal settling time of significantly less than 100 seconds and a further consistent stable measurement signal. The measurement signal dynamics of approx. 58 mV per factor 10 of concentration change is given for the measured variables pH and K+. For the measured quantities of NO3- and H2PO4- , the measurement signal dynamics are lower.

This paper investigates four different mobile robots with respect to their drivingcharacteristics and soil preservation properties in an agricultural environment.Thereby, robots of classical design from agriculture as well as systems from spacerobotics with advanced locomotion concepts are considered to determine theindividual advantages of each rover concept with respect to the application domain.Locomotion experiments were conducted to analyze the general driving behavior,tensile force, and obstacle‐surmounting capability and ground interaction of eachrobot. Various soil conditions typical for the area of application are taken intoaccount, which are varied in terms of moisture and density. The presented workcovers the specification of the conducted experiments, documentation of theimplementation as well as analysis and evaluation of the collected data. In theevaluation, particular attention is paid to the change in driving characteristics underdifferent soil conditions, as well as to the soil stress caused by driving, since soilquality is of critical importance for agricultural applications. The analysis shows thatthe advanced locomotion concepts, as used in space robotics, also have positiveimplications for certain requirements in agricultural applications, such as maneuver-ability in wet conditions and soil conservation. The results show potential for designinnovations in agricultural robotics that can be used, to open up new fields ofapplication for instance in the context of precision farming.