A method about state-space representation and location estimation by computational geometry
Yi Zhang, Mengyin Fu, Meiling Wang · 2014
This paper analyzes the accuracy concerns of self-positioning of some unmanned ground vehicle that is undertaking simultaneous localization and mapping. The environment information description provided by vehicle sensor usually has strong geometric feature. Thus, the paper puts forward a method with geometric feature for simultaneous localization and mapping environment description. After analyzing the uncertainties in this type of environment description, the paper uses computational geometry to model and describe the uncertainties caused by measuring error of the sensor. At last, by using computational geometry, the paper proposes a location estimation algorithm that helps to reduce the impact of measuring errors on calculation coordinates.