Een grote toekomst voor kleine robots in open teelten

Een evaluatie wordt gemaakt na 1 jaar met ervaringen met verschillende kleine landbouwrobots, waarna de verdere ontwikkelingen voor de toekomst ter sprake kome

Herkenning en bestrijding van ridderzuring met een robot

Ridderzuring (Rumex obtusifolius L.) is een veelvoorkomend en lastig te bestrijden onkruid dat vooral biologische melkveehouders grote problemen bezorgt. Op initiatief van de sector wordt daarom een robot ontwikkeld die geheel zelfstandig ridderzuring opspoort en vernietigt

The ModCom modular simulation system

Simulation models of agro-ecological systems are typically written in a manner that precludes reusability of parts of the model without a significant amount of familiarity with and rewriting of existing code. Similarly, replacing a part of a model with a functionally equivalent part from another model is typically difficult. The objective of this study was to develop a method to enable the assembly of simulation models from previously and independently developed component models. Recent advances in software engineering have enabled the development of software applications from smaller parts (called components) on the basis of an abstract decomposition of the relevant domain (called a framework). Based on a requirements analysis of existing simulation models we developed the ModCom simulation framework. ModCom provides a set of interface specifications that describe components in a simulation. ModCom also provides implementations of the core simulation services. The framework interfaces use well-defined binary standards and allows developers to implement the interfaces using a broad range of computer languages. Using this framework, simulation models can be assembled by connecting component models in much the same way that Lego blocks are put together to assemble a house. ModCom thus allows modelers to create models and modeling tools that are easily exchanged (in binary form or source code) with colleagues across the hall or across the globe

Weed Detection Using Textural Image Analysis

The objective of the work described here was to detect broad-leaved weeds in grassland. We used textural image analysis to detect weeds in grass. In the textural analysis, images were divided in square tiles, which were subjected to a 2-D FFT. The power of the resulting spectrum was found to be a measure of the presence of coarse elements (weeds). Application of a threshold made it possible to classify tiles as containing only grass or as containing a weed. A weed was assumed to be detected when a sufficient number of adjacent tiles were classified as containing weed material. The algorithm has a success rate of 94%

Hielke is a Bayesian, balancing field robot

Driven by the success of the previous events in Wageningen in 2003, 2004 and 2005 and the Field Robot Event hosted by Hohenheim University in Stuttgart, Germany in 2006, Wageningen University organized the 5th Field Robot Event on June 14-16, 2007. This event was accompanied by a workshop and a fair where the teams were able to present their robots. Teams also had to write a paper describing the hard- and software design of their robot. These papers collected in this ‘Proceedings of the 5th Field Robot Event’ are a very valuable source of informatio