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

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Conclusions system, parameter adjustments need to be replaced by a more systematic method. The sensors utilised during the tests are intended for industrial detection. However, it needs to be confirmed that intensive application in hard on the field conditions will not cause any negative influence on their robust work. The digital RGB fibre optic sensor CZ-H35S uses a light emitter with a spot diameter of 4.5 mm. Parallel implementation of several sensors covering an area at least as wide as the laser sensor is required for reliable detection. The developed prototype for intra-row weed control could be used in future for accurate measurement of the torque. The potentials for optimisation of the torque are highly influenced by the size and shape of the duckfoot knives. Their behaviour in different conditions needs to be investigated. Change of the soil moisture content, change of the hoeing speed, change of the forward speed, change of the hoeing depth are only several aspects which can deliver new substantial knowledge very important for further development of the mechanical intra-row weed control. A possibility for improvement of the controlling algorithm will be substitution of the currently used P with PI, PID or another more sophisticated one, like a fuzzy or neural network based algorithm. Finally, testing of the intra-row weeding system combined with an inter-row system in field condition will be of great importance. 126
8 References References Agrios, G. N. 1988. Plant pathology. 3rd ed. Academic press, Inc. New York. p.803 Albrecht, H. 2005. Development of arable weed seedbanks during the 6 years after the change from conventional to organic farming. Weed Research 45[5]. pp.339-350 Altieri, M. A. and Letourneau, D. K. 1982. Vegetation management and biological control in agroecosystems. Crop production 1. pp.405-430 Anonymous 1. 2007. Mutsaers QI. Available at: http://www.duijndam.nl. Accessed June 25, 2007 Anonymous 2. 2007. Robocrop Vision Guidance System. Available at: http://www.garford.com. Accessed June 25, 2007 Anonymous 3. 2007. Finger weeder. Available at: http://www.weedmachine.co.uk. Accessed June 25, 2007 Anonymous 4. 2007. Pro Engineer. Available at: http://www.ptc.com. Accessed June 25, 2007 Ascard, J. 2007. Torsion weeder. Available at: http:// www.ewrs.org. Accessed June 25, 2007 Åstrand B. 2002. An agricultural mobile robot with vision-based perception for mechanical weed-control. Autonomous robots 13. pp.21-35 Åstrand, B. 2005. Vision based perception for mechatronic weed control. Chalmers University of Technology: Department of Computer Sciences and Engineering. p.107 127
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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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Materials and methods become a poss
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Materials and methods environments
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Materials and methods dimensions ne
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Materials and methods (PFM). As the
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Materials and methods A command sig
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Materials and methods The drive con
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Materials and methods Another tool
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Results and discussion 58 Figure 5.
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Results and discussion objects. Acc
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Results and discussion Plant positi
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Results and discussion Plant positi
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Results and discussion 70 5.1.4 Dis
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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 112 and 113: Results and discussion As the size
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: 7 Conclusions Conclusions The prese
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 169: Personal data Education About the a
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