About the book
This book concerns autonomous mobile mapping robots capable of digitizing the surrounding environment in the form of a map easily interpretable by humans. This functionality is related to fundamental algorithmic challenges in the mobile robotic domain.
Such machines can execute the autonomous mission in unknown and harsh environments; thus, they can help humans in decreasing the time of digital map delivery. Many algorithmic challenges have to be addressed, such as Simultaneous Localisation and Mapping assuming low energy onboard computers. LiDAR and VISUAL odometry are t candidates for initial trajectory estimation. Furthermore, a robust Graph SLAM approach can efficiently reduce incremental odometry error. Moreover, recent advances in Deep Neural Networks DNN applied for image and LiDAR data processing and analysis (segmentation and classification) are also crucial. DNN can provide necessary information to improve autonomous task execution. This book will address the problem of path planning and autonomous task execution as large-scale mobile mapping applications. For this reason, some practical implementations are provided. This book will intend to provide the reader with a comprehensive overview of the current state-of-the-art in autonomous mobile mapping robots.