Augmented vector field navigation cost mapping using inertial sensors
Carregando...
Data
Título da Revista
ISSN da Revista
Título de Volume
Editor
Universidade Federal de Minas Gerais
Descrição
Tipo
Artigo de evento
Título alternativo
Primeiro orientador
Membros da banca
Resumo
In outdoor field robotics, considering the environmental characteristics is key to improving the efficiency of autonomous navigation. In this context, identifying rough terrain can significantly increase the reliability of operations. This paper addresses the problem of mapping the navigation cost associated with uneven outdoor terrains. We propose an augmented vector field representation obtained only with the use of inertial sensors. The map is determined considering characteristics such as roughness and slope. Experiments were carried out with different robots in real-world environments presenting different terrain characteristics to analyze the quality and efficiency of the mapping process. Results show that the obtained navigation cost maps provide a reliable indication of the ground characteristics of outdoor environments and can be used in the path planning stage.
Abstract
Assunto
Sistemas lineares
Palavras-chave
Robot navigation, Cost Function , Vector Field , Inertial Measurement Unit , Navigation Cost , Outdoor Environments , Path Planning , Autonomous Navigation , Root Mean Square Error , Flat Surface , Angular Velocity , Gaussian Process , Kriging , Pathfinding , Vector Magnitude , Distance Information , Vibration Signals , Surface Slope , Roughness Measurements , Representation Of The Environment , Dijkstra’s Algorithm , Roughness Level , Terrain Map , Terrain Slope , Inertial Data , Efficient Navigation , Destination Point , Vertical Acceleration , Robot Navigation , Two-dimensional Grid , Covariance Function
Citação
Curso
Endereço externo
https://ieeexplore.ieee.org/document/8981572