Journal of Robotics, Networking and Artificial Life
Vol. 6(3); December (2019), pp. 148–151
DOI: https://doi.org/10.2991/jrnal.k.191202.002; ISSN 2405-9021; eISSN 2352-6386
https://www.atlantis-press.com/journals/jrnal

Research Article

Soil Compaction and Rolling Resistance Evaluation of aLocomotion System with an Adjustable Contact
Patch for a Grape Transporting Robot
Enrico di Maria*, Kazuo Ishii
Department of Human Intelligence System, Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology,
2-4 Hibikino, Wakamatsu-ku, Kitakyushu 808-0196, Japan

ARTICLE INFOABSTRACTArticle History

Soil compaction is a form of soil degradation which causes soil erosion, drainage difficulties, and loss of nutrients. To mitigate
this issue, in agricultural farms several methods have been adopted. In this paper, the preliminary study of a locomotion systemwith adjustable contact patches is proposed. Aim is to reduce the compaction and optimize the rolling resistance of a grapetransporting robot used in vineyard. A Finite Element Method (FEM) model supported by experimental results is developed tostudy the system.

Received 17 November 2018Accepted 20 December 2018
Keywords
Soil compaction
rolling resistancefinite element method
cone penetrometer© 2019 The Authors. Published by Atlantis Press SARL.
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

1. INTRODUCTION
Soil compaction of agricultural soil is the result of the increase
in mechanization and the usage of heavy vehicles exerting highforces onto the soil. As a porous material, soil consists of a solidpart which includes pores containing air or water. Excessive compression causes the reduction of pore space and the loss of air andwater, important for plants roots growth, and determines infiltration difficulties, loss of nutrients and soil erosion. Soil compaction resulted to be related to a significant reduction in the yield,
and it was estimated a crop yielding reduction of 25–50% in some
districts of Europe and North America [1]. To solve these issues
many methods have been proposed, with different results and different costs [2]. The problem can be addressed by direct interventions, such as subsoiling and plough, or by avoiding compaction
using low ground pressure tyres, tracked tractors or Controlled
Traffic Farming (CTF). Avoiding the compaction resulted to be
the best solution in terms of cost benefits. With CTF, not only
compaction itself is avoided, but energy consumption is contained because of the lower rolling resistance of vehicles on permanent traffic lane [2]. Different levels of mechanization can beadopted, depending on the type of farm, and soil compaction isoften neglected by farmers.
Target of this work is the canopied vineyard, in which the trees
form a roof and the small and closed environment makes moredifficult a full mechanization. Here harvester machines are rarelyused, unlike the espalier vineyards where big harvester machines*Corresponding author. Email: e.dimaria.srt@gmail.com

are widely used. Usual tractors do not improve the harvesting process, but they still cause a lot of compaction.
The system proposed here consists of an autonomous mobile kart
aimed to optimize the rolling resistance while avoiding the soil
compaction. It consists of four small track modules which can bepartially lifted so as to reduce their contact patch and act as a wheel,
depending on the soil conditions and vehicle payload (Figure 1).
Tracks are more suited for soft or wet soils, while wheels show
better performance on hard soils.
In this paper, the system is studied in terms of soil compaction
and Rolling Resistance (RR), evaluated by empirical equations
and a Finite Element Method (FEM) model. FEM simulations
have been widely used for RR evaluation on soft and hard soils [3].
Experiments in the field are carried out to find some of the parameters required for modelling the soil with FEM.
Empirical equations for RR evaluation, derived from Terramechanics,
are considered in the second section. In the third section, the experiments carried out in the vineyard are explained. These results,
together with a non-linear regression equation, are used in Section 4for evaluating the soil Young moduli and developing the FEM
model for the analyses. Finally, in Section 5, the simulations arecarried out and the results explained.

Figure 1 | System configurations in track and wheel mode.

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2. ROLLING RESISTANCE ON SOFT SOILS

3. EXPERIMENTS IN THE VINEYARD

Rolling resistance on soft terrains can be seen as the work done incompacting the soil and making a rut of area A and depth z [4], as
expressed by Equation (1):Soil strength measurements are carried out in a vineyard in theSouth of Italy, at Latiano city, in Puglia region.

z0		     Rl = bl ò pdz (1)0where z is the rut depth, p the pressure, b the contact patch width,l the contact patch length of the track and R the rolling resistance.
In case of wheel, the length considered is the distance travelled by
one revolution. The pressure-sinkage relation proposed by Bekker
needs a series of empirical parameters, such as: the cohesion modulus kc, the frictional modulus kɸ and the exponent of sinkage n.
These parameters are determined by means of the Bevameter test[4]. Because the equipment required is big and the interpretation of
the results is not simple, often the usage of the Cone Penetrometer(CP) is preferred to estimate the rolling resistance and performance of off-road vehicles [5]. CP is a portable device to measure the strength of the soil. It consists of a circular cone at theend of a metal stick, equipped with a load cell for measuring theforce required to put the cone into the ground [4]. The parameterobtained is the Cone Index (CI), measured in kPa. Based on the CI,
the following empirical equations (2) and (3) for estimating the RR
on soft terrains have been proposed for track vehicles [6]:	    Cn =

æ 0.45öCI ´ b ´ l, RR = W ç+ 0.045÷ W
è Cnø

(2)

Hand-held digital CP SC900 developed by Spectrum Tech­nologies(3600, Thayer Court, Aurora, IL 60504, USA) is used. This sensor
allows to investigate the soil until a depth of 45 cm and a CI of 7000
kPa. Moisture sensor VG Meter 200 (583, Vegetronix Inc, Riverton,UT 84065, USA) is adopted for measuring the volumetric watercontent percentage. Moisture content affects soil behavior and rolling resistance considerably, and for this reason it is important tomonitor it in the analysis.
The measurements are taken with profiles 6 m apart of each othermade of nine points each, as in Figure 3, so as to get a profile of compaction along the path width, with a total of 63 measurements. Thedistance between the trees is 2 m, while the space among each measurement point is 22 cm. The points are in the middle between thetrees of each path side for avoiding their roots. Because the average
CI for the first 15 cm is widely used for rolling resistance evaluation[5], a depth of 15 cm is considered here. On the wheel tramlines
some of the measurements could not be completed because theresistance exceeded the limit of the sensor. In the analysis a value of7000 kPa (sensor limit) is considered for those points.
The results in terms of range of CI measured and profile along theroad are reported in Figures 4 and 5 respectively. Moisture content
average is of 6.5% in a range of [2–17%]. High variability in the overall CI results is due to the higher compaction at the wheel tramlines,
as it can be seen from the two peaks in the strength profile.

And for wheel vehicles [7]:	    C = CI × b × D , RR = W  1.2 + 0.04 n CWn(3)where Cn is the track numeric, b and l the contact patch width andlength respectively, D the wheel diameter, W the weight supported
from each wheel or track, and RR the rolling resistance. As a firsttentative choice for the design, the product HS-200 developed by
Shangai Puyi Industrial Co. (3585 Fengzhe Road, Fengxian District,Shanghai, China) is considered. Main dimensions and load bearing
are shown in Table 1.
Considering this track module and a vehicle weight of 400 kg, fora CI between 500 and 7000 kPa the comparison in terms of RR
between track mode and wheel mode is shown in Figure 2.

Figure 2 | Rolling resistance comparison between wheel and track modefor different soil strengths.

As expected, on soft soil tracks outperform wheels, while on hardsoil wheels have better performance.
The difference of performance between the two modes depends on
track sizes and vehicle weight, and in the final design a set of bestparameters has to be decided in order to maximize this difference
and minimize the RR.
Table 1 | HS-200 Track module
Ground contact length (mm)Width (mm)Outer sprocket diameter (mm)Load bearing (kg)400
200370100Figure 3 | Experimental layout.

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experimentally. Tentative values taken from the literature for softand hard clay soils are used. Additional experiments in the field
are needed to tune properly these values and define a specific soil.
The FEM analysis discussed is an improved version of the analysis
in di Maria and Ishii [10], where only static simulations are performed and RR resulted too underestimated.
A transient analysis is performed to take into account also thedynamic effects. The simulation consists of towing a wheel and a
track on the agricultural soil modeled by FEM. The vertical weightis 1000 N with a velocity of 15 mm/s. To improve the time efficiencyof each simulation a 2-D model is adopted instead of a 3-D model.

5. RESULTS AND DISCUSSION

Figure 4 | Cone index overall results.

Figure 5 | Soil strength profile AVG 15 cm.

4. SOIL MODELLING AND SIMULATIONS
Soil under stress shows an elastoplastic behavior. Drucker-Prager
criterion (DP), outer cone approximation of the Mohr-Coulomb
criterion, is used in this work [3].
A strategy adopted for modelling the soil using FEM is to divide it
into layers. Based on the values of CI got during the experiments,
three layers are modeled. First 2.5 cm with low strength, 2.5–7.5 cm
with medium strength and from 7.5 to 50 cm with high strength.
Density and Young Modulus E (in case of soils also called Modulusof deformation) are different in each layer. The relation between CIand E for cohesive and non-cohesive soils is provided by Mel’nikov
and Boldyrev [8], by the non-linear regression equation shown inEquation (4), based on the soil classes classification as in Mel’nikov
and Boldyrev [8], using a soil type function Ic. From the average
CI of the experiments and considering a clay soil class, the Youngmoduli for the three layers are estimated.	  

E = 2460 − 6005 × I c − 5811 × I c2
+ (1084 − 1511 × I c + 1090 × I c2 ) × CI

(4)

The estimated Young moduli for the three layers are: 0.5, 4.35 and13.1 MPa, for the first, second and third layer respectively.
As a first step soil is considered as an isotropic elastic medium [9],with the Young moduli reported above and a Poisson ratio of 0.3.
The model is then completed by a bilinear isotropic hardening rule,and uniaxial compressive and tensile strength and biaxial compressive
strength for the DP criterion. These last values should also be foundThe outputs evaluated by the FEM analysis are: the sinkage, the RR
and the soil stress. For the wheel mode the steady-state value of thesinkage is 11.3 mm with a RR between 83 and 86 N. Soil stress hasa peak of 62.7 kPa at a depth of 2.5 cm. This value decreases soonafter the first layer and becomes <30 kPa at a depth of about 10 cm.
For the track mode, the rut depth is 1.5 mm and RR is between
75 and 80 N. The peak of soil stress is 17.2 kPa at the first layer. Alsoin this case it decreases at the deeper layers. At a depth of 25 cm
the stress is about 15.5 kPa for the wheel and 11 kPa for the track.
This behavior is in agreement with other analyses [2], for whichthe contact pressure affects mainly the first layers, while the stressat the deeper layers depends mainly on the vertical load. Values of
RR are close for both the locomotion modes. With an average CI of1800 kPa we can expect close values of RR for the two modes, withthe size and weight chosen for the track module, as seen from theempirical equations in Section 2. But the values are still low andfurther model refinements are required.

6. CONCLUSIONS AND FUTURE WORKSIn this paper, the preliminary study for the development of amobile robot with an adjustable contact area was presented. Aimof the robot is to transport the grape in the vineyard, in order tosupport the harvesting process by optimizing the energy consumption while reducing the soil compaction. The experimental resultspresented in Section 3 had a double use. At first they showed theeffect of the tractors traffic in the vineyard, where the wheel tramlines were more compacted than the surrounding areas. Second,
they served for estimating the Young moduli of the three soil layers
in the FEM model. This model is used as a tool for the design.
The results obtained from the analysis are in agreement with theexpectation, but further experiments with a real pull test in thevineyard are required to tune the parameters of the model and get
more precise results. After this tuning, the model can be used tocarry out an analysis for choosing the best set of design parameters
in terms of track module size and robot maximum weight.

CONFLICTS OF INTEREST
The authors declare they have no conflicts interest.

E. di Maria and K. Ishii / Journal of Robotics, Networking and Artificial Life 6(3) 148–151

ACKNOWLEDGMENTS
We thank our friend Daniele Ciccarese for allowing us to carry out
the experiments in his farm and for his support.

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Proceedings of the 2019 International Conference on Artificial
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Authors Introduction
Mr. Enrico di Maria

Prof. Kazuo Ishii

He received his Master degree in MechanicalEngineering from the Department ofInnovation Engineering, at University ofSalento, Italy, in 2016. He is pursuing thePhD at Kyushu Institute of Technology,
Department of Life Science and Systems
Engineering, under the supervision of Prof.
Kazuo Ishii. His research interests include
off-road vehicles and agricultural robots.

He received the PhD degree from theDepartment of Naval Architecture
and Ocean Engineering, University ofTokyo, Tokyo, Japan, in 1996. He is currently a Professor with the Departmentof Human Intelligence Systems, and theDirector of the Center for Socio-RoboticSynthesis, Kyushu Institute of Technology,
Kitakyushu, Japan. His research interests include underwaterrobots, agricultural robots, roboCup soccer robots and intelligent systems.