Development of a novel mechatronic system for mechanical weed ...

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Results and discussion As the size of the searching area depends on the average plant size in the field, theoretically it could be almost as big as the distance between plants. Hence, the optimal point for the execution will be the moment, when the plant detection unit reaches the middle point between two searching areas. A value approximately equal to double of the average intra-row distance between plants can be defined as a necessary distance between the plant detection unit and the plane in which the hoe is positioned. Such an approach is determined by the software solution because it requires the position of two following plants for calculation of the forward speed (see Figure 5.21). 94 Figure 5.21 Definition of the required distance between the plant detection unit and the plane in which the hoeing tool is placed
Results and discussion Based on indicated requirements the optimal distance can be identified. For the average intra-row distance between plants of 200 mm optimal distance can be calculate as: ⎛ 2 1 ⎞ 13 Dsens −hoe = ⎜ + 1+ ⎟d = d ⎝ 3 2 ⎠ 6 for d= 200 mm (5.16) D − = 433,33 mm ≈ 435 mm (5.17) sens hoe This value is optimised for the hoeing tool with three arms, three cuts between two successive plants, average intra-row distance about 200 mm and initial position of the system as shown in Figure 5.19. Using the same approach presented in this chapter, there is a possibility to calculate the optimal distance between the detection unit and the plane in which the hoeing tool is placed, for other hoeing strategies with different number of arms, increased or decreased number of cuts between successive plants and alternative intra-row distances between plants. As mentioned, the software solution requires centre positions of two following plants for calculation of the forward speed. Using such a method of speed acquisition, the necessity for implementation of an additional hardware system for speed measurement was avoided. Of course, application of an additional hardware would simplify the software, because calculation of the forward speed would not be necessary, and it would allow shortening of the distance between the detection unit and the plan in which the hoeing tool is placed for one average intra-row distance. To avoid additional investments into speed measuring hardware, whose costs grow with the required accuracy, especially in low speed ranges, the alternative of speed measurement with software was chosen. 95
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Institut für Landtechnik der Rhein
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Development of a novel mechatronic
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Kurzfassung Entwicklung eines neuar
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Acknowledgements Acknowledgements M
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Table of contents Table of contents
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Glossary of abbreviations and symbo
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Symbol Unit Description Mmmax Nm Ma
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Symbol Unit Description Glossary of
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ωold ωout rad s -2 Latest rotatio
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Introduction The most frequently us
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Introduction application that had p
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Introduction be to go from a system
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Introduction limited and environmen
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Introduction than 40 years before g
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Introduction techniques. It is know
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Introduction Sowing and planting al
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Introduction Inter-row weeding syst
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Introduction 18 Figure 1.3 Inter-ro
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State of the art 20 Figure 2.1 a) F
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State of the art cylinder rotates a
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State of the art 1998). This device
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State of the art 26 2.2 Detection o
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State of the art The fluorescence s
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Definition of the problem and resea
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4 Materials and methods 4.1 Detecti
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Materials and methods Figure 4.1 a)
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Materials and methods Figure 4.3 a)
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4.1.2 Data acquisition 4.1.2.1 Hard
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4.1.4 Test objects Materials and me
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Page 63 and 64: Materials and methods environments
Page 65 and 66: Materials and methods dimensions ne
Page 67 and 68: Materials and methods (PFM). As the
Page 69 and 70: Materials and methods A command sig
Page 71 and 72: Materials and methods The drive con
Page 73: Materials and methods Another tool
Page 76 and 77: Results and discussion 58 Figure 5.
Page 82 and 83: Results and discussion objects. Acc
Page 84 and 85: Results and discussion Plant positi
Page 86 and 87: Results and discussion Plant positi
Page 88 and 89: Results and discussion 70 5.1.4 Dis
Page 92 and 93: Results and discussion Connection b
Page 94 and 95: Results and discussion 76 5.2.1 Opt
Page 96 and 97: Results and discussion xmi1 = ( RLA
Page 98 and 99: Results and discussion With the inv
Page 100 and 101: Results and discussion 82 Horizonta
Page 102 and 103: Results and discussion 84 5.2.4 Sel
Page 104 and 105: Results and discussion 86 5.2.5 Dis
Page 106 and 107: Results and discussion Conventional
Page 108 and 109: Results and discussion Since the fi
Page 110 and 111: Results and discussion To avoid con
Page 114 and 115: Results and discussion 96 5.3.4 Alg
Page 116 and 117: Results and discussion 98 V = zc( t
Page 118 and 119: Results and discussion corresponds
Page 120 and 121: Results and discussion 102 5.3.6 Me
Page 122 and 123: Results and discussion hoeing accur
Page 124 and 125: Results and discussion between the
Page 126 and 127: Results and discussion distance fro
Page 128 and 129: Results and discussion Distribution
Page 130 and 131: Results and discussion cuts are ran
Page 132 and 133: Results and discussion Forward spee
Page 134 and 135: Results and discussion x [mm] Distr
Page 136 and 137: Results and discussion The experime
Page 139 and 140: 6 Summary Summary Neither a mechani
Page 141 and 142: Summary The third part of the work
Page 143 and 144: 7 Conclusions Conclusions The prese
Page 145 and 146: 8 References References Agrios, G.
Page 147 and 148: References in California's Sacramen
Page 149 and 150: References Johnson, W C and Mullini
Page 151 and 152: References Schans, D. v. d. et al.
Page 153 and 154: List of figures List of figures Fig
Page 155 and 156: List of figures Figure 5.24 Scheme
Page 157 and 158: Plant position 9 Appendix Table 9.1
Page 159 and 160: Plant position Table 9.3 Detection
Page 161 and 162: Plant position Table 9.5 Detection
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Plant position Table 9.7 Detection
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Personal data Education About the a
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