Wearable Sensors and Their Application in Urban Landscape Design

A wearable multi-sensor perception system for urban landscape design is developed in response to mobile, wearable sensors’ low positioning accuracy and limited environmental description capability based on a single sensor in urban landscape design. Firstly, an omnidirectional four-wheeled Mecanum mobile platform is constructed. Secondly, the Real-Time Appearance-Based Mapping (RTAB G MAP) algorithm is analyzed. Finally, based on the fused data, the traditional wearable sensor navigation framework is optimized to achieve autonomous navigation. The results show that this system’s wearable sensor perception scheme can accomplish both two-dimensional and three-dimensional landscape design for urban landscape design, improve the environmental description capability, and significantly improve the positioning accuracy of wearable sensors through the fusion of extended Kalman filtering, ensuring navigation accuracy.