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The two main goals of this research are the development of a harvesting robot and the improvements brought in the present high-wire cultivation cucumber plant system. The mobile robot consists of a vehicle for course positioning of the robot, a manipulator and an end-effector. Aspects like working time, number of robots in a standard 2-ha cucumber nursery, and technologies used to detect, classify and locate the cucumber within its environment will also be discussed in this paper.

Sweet pepper production is characterized by large fluctuations in fruit yield in time. These fluctuations have a detrimental effect on the operational planning of labor at nursery level as well as on the efficiency of the supply chain. At the same time, the dependence of temperate zone greenhouse horticulture on fossil fuel needs to be reduced for long-term viability. Growers are aware of the fact that by modifying the indoor temperature, these fluctuations can be influenced, but the dynamics involved are complex and hard to master. Therefore, in practice the degree of control achieved is limited and sometimes obtained at the cost of a higher energy consumption. In this research, using the framework of optimal control theory and employing a sweet pepper production model, alternative temperature strategies were searched for with the aim of reducing production fluctuations and using a minimum amount of energy. The results obtained in this research indicate that fluctuations in sweet pepper production can be reduced using optimized temperature strategies, either by controlling production in one compartment or by controlling production in opposite phase in two compartments. By doing so, energy savings of 10% can be obtained. In contrast with standard horticultural practice, a striking feature of the optimized temperature trajectories is their considerable variation in time.

Algorithms for environmental control in livestock buildings have to be tuned for optimum response of actuators. For tuning, a simple, but dynamic, climate model for a pig house was formulated and validated to predict theenvironmental changes in a pig house with natural ventilation under varying conditions, A control algorithm was included in the model and tuning of the algorithm has been performed with the model. The tuned algorithm wasimplemented in a climate controller and data on the results are presented. It was concluded that the model can be used to simulate room temperature and carbon dioxide concentration in heated pig houses with natural ventilation. The dynamics as well as the actual levels of climate parameters showed agreement between simulation results and actual results. The model can be used to find gain factors and time constants for PID-controllers in algorithms for control of room temperature, air quality, and ventilation rate in natural ventilated pig houses. This would enhance fast and accurate tuning controllers in livestock buildings with natural ventilation as compared to on-site hand tuning.Keywords. Natural ventilation. Control, Model, Swine.