Publications:Infrastructure Mapping in Well-Structured Environments Using MAV
From ISLAB/CAISR
| Title | Infrastructure Mapping in Well-Structured Environments Using MAV |
|---|---|
| Author | Yuantao Fan and Maytheewat Aramrattana and Saeed Gholami Shahbandi and Hassan Mashad Nemati and Björn Åstrand |
| Year | 2016 |
| PublicationType | Journal Paper |
| Journal | Lecture Notes in Computer Science |
| HostPublication | |
| Conference | 17th Annual Conference on Towards Autonomous Robotic Systems, TAROS 2016, Sheffield, United Kingdom, 26 June-1 July, 2016 |
| DOI | http://dx.doi.org/10.1007/978-3-319-40379-3_12 |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:948972 |
| Abstract | In this paper, we present a design of a surveying system for warehouse environment using low cost quadcopter. The system focus on mapping the infrastructure of surveyed environment. As a unique and essential parts of the warehouse, pillars from storing shelves are chosen as landmark objects for representing the environment. The map are generated based on fusing the outputs of two different methods, point cloud of corner features from Parallel Tracking and Mapping (PTAM) algorithm with estimated pillar position from a multi-stage image analysis method. Localization of the drone relies on PTAM algorithm. The system is implemented in Robot Operating System(ROS) and MATLAB, and has been successfully tested in real-world experiments. The result map after scaling has a metric error less than 20 cm. © Springer International Publishing Switzerland 2016. |
