Fuzzy evaluation method for environmental factors affecting a mobile robot's sensor system in view of design for logistics

Background: The paper is devoted to mobile robot design problems with a focus on exteroceptive sensor systems for operation in a mixed environment (indoor with outdoor possibility). With a view to the design for logistics, the important concerns are, among others, minimization of the number of parts, reduction of weight, and reduction of dimensions. One of the challenges that arise here is the consideration of environmental factors, which vary among different application systems. It is necessary to reach a compromise between operational requirements and costs involved. Therefore, the relevance of the environmental factors should be evaluated to divide them into those that should be addressed and those that can be ignored. This will translate into the selection of sensors in sufficient quantity to provide the requirements without excessiveness. Methods: We propose a novel three-stage method for assessing the relevance of environmental factors using fuzzy logic with occurrence, recovery, and impact level consideration. We take into account the impact level of each factor on the entire sensor system, restoration of functions lost completely or partially as a result of the factor (recovery), and the frequency of factor occurrence. Results: The identified environmental factors, evaluated in term of their relevance are hierarchized from the most to the least relevant. The application of the method is presented on the basis of an autonomous forklift for indoor and outdoor use. Conclusions: Based on the proposed method, it is possible to design a sensor system with consideration of any operation environment. The three-criteria method allows evaluation of any factor influencing sensor system on a five-point scale, both in terms of occurrence and severity (understood as impact level effect and recovery time). By evaluating the factors and thus prioritizing them using our method, only the most important factors from the designer's point of view can be taken into account. This can translate into minimizing the number of sensors and thus cost reduction and shorter implementation time.