TOOLS STUDY FOR HAZARDS IDENTIFICATION IN SYSTEMS OF AUTONOMOUS ROBOTS IN FARMING

Abstract: Autonomous Unmanned Aerial Vehicles (UAVs) in agriculture are increasingly in demand to reduce cost, labour and increase effectiveness and quality in farming. However, it is necessary to improve reliability for this technology to perform its full potential without harming humans, animals or the environment. The reliability increases by identifying the hazards and mitigating them. Therefore the risks are identified, analyzed and mitigated using analysis tools. Two different methods are used to analyze and reduce hazards, and each method utilizes various analysis tools. In addition, redundancy and preventive action are proposed to eliminate or minimize the danger. This thesis identifies risks by studying and reviewing a generic use-case from the AFarCloud project and compares the two hazard analysis methods to determine which method provides the most reliable result.