Preliminary laboratory test on navigation accuracy of an autonomous robot for measuring air quality in livestock buildings

Air quality in many poultry buildings is less than desirable.However,the measurement of concentrations of airborne pollutants in livestock buildings is generally quite difficult.To counter this,the development of an autonomous robot that could collect key environmental data continuously in livestock buildings was initiated.This research presents a specific part of the larger study that focused on the preliminary laboratory test for evaluating the navigation precision of the robot being developed under the different ground surface conditions and different localization algorithm according internal sensors.The construction of the robot was such that each wheel of the robot was driven by an independent DC motor with four odometers fixed on each motor.The inertial measurement unit(IMU)was rigidly fixed on the robot vehicle platform.The research focused on using the internal sensors to calculate the robot position(x,y,θ)through three different methods.The first method relied only on odometer dead reckoning(ODR),the second method was the combination of odometer and gyroscope data dead reckoning(OGDR)and the last method was based on Kalman filter data fusion algorithm(KFDF).A series of tests were completed to generate the robot’s trajectory and analyse the localisation accuracy.These tests were conducted on different types of surfaces and path profiles.The results proved that the ODR calculation of the position of the robot is inaccurate due to the cumulative errors and the large deviation of the heading angle estimate.However,improved use of the gyroscope data of the IMU sensor improved the accuracy of the robot heading angle estimate.The KFDF calculation resulted in a better heading angle estimate than the ODR or OGDR calculations.The ground type was also found to be an influencing factor of localisation errors.

Optimum insulation thickness for the sandwich structure livestock buildings external envelopes in different climate regions of China

Determining the optimum insulation thicknesses of external envelopes for livestock buildings are one of the most effective metrics to decrease energy requirements.This study was carried out to determine the optimum insulation thicknesses for livestock buildings in different climate zones,to examine the effects of insulation thickness and material(foam glass,mineral wool,expanded polystyrene,foamed polyurethane,foamed polyvinyl chloride,and expanded polyethylene)on life cycle total cost,life cycle savings,and payback period.The finishing pig houses and laying hen buildings with sandwich wall structures(color steel laminboard)in five typical cities were studied using the degree-days method with economic models.Optimal insulation thicknesses ranged from 0.05 m to 0.25 m and 0.02 m to 0.24 m in finishing pig houses and poultry buildings,respectively;the life cycle total costs ranged from 16.49 to 37.98$/m2 and 13.37 to 36.84$/m2;the life cycle savings ranged from 29.13 to 220.60$/m2 and 0 to 202.13$/m2;and the payback period ranged from 1.11 to 5.81 years and 1.19 to 20.76 years,respectively.Foamed polyurethane provided the highest life cycle savings,while foam glass had the lowest.In this research,the insulation thicknesses for the sandwich structure livestock buildings external envelopes are optimized,and the energy saving can be obtained by using proper insulation thickness in different regions.Furthermore,it can increase the knowledge about energy consumption in the livestock buildings and the results can be also a useful tool for farmers.

Evaluating droplet distribution of spray-nozzles for dust reduction in livestock buildings using machine vision

Previous studies have demonstrated the negative effects of sub-optimal air quality on profitability,production efficiency,environmental sustainability and animal welfare.Experiments were conducted to assess potential environmental improvement techniques such as installing oil-spraying systems in piggery buildings.The developed spray system worked very well and it was easy to assemble and operate.However,before selecting the most suitable spray heads,their capacity to uniformly distribute the oily mixture and the area covered by the spray heads had to be assessed.Machine vision techniques were used to evaluate the ability of different spray heads to evenly distribute the oil/water mixture.The results indicated that the best coverage was achieved by spray head No.4 and spray head No.1 which covered 79%and 67%of the target area,respectively.Spray distribution uniformity(variance)value was the lowest for spray head No.4(0.015).Spray head No.3 had the highest variance value(0.064).As the lowest variance means higher uniformity,nozzle No.4 was identified as the most suitable spray head for dust reduction in livestock buildings.