Abstract
We present a single vision-based, self-localization method for autonomous mobile robots in a known, indoor environment. This absolute localization method is landmark assisted, therefore, we propose an algorithm that requires the extraction of a single landmark feature i.e., the length of a known edge. Our technique is based on measuring the distance from two distinct, arbitrarily
positioned landmarks in the robot’s environment, the locations of which are known a priori. A single camera vision system is used to perform distance estimation. The developed framework is applied to tracking a robot’s pose,
i.e., its position and orientation, in a Cartesian coordinate system. The position of the robot is estimated using a bilateration method, while its orientation calculation utilizes tools from projective geometry. The validity and feasibility
of the approach are demonstrated through experiments.
positioned landmarks in the robot’s environment, the locations of which are known a priori. A single camera vision system is used to perform distance estimation. The developed framework is applied to tracking a robot’s pose,
i.e., its position and orientation, in a Cartesian coordinate system. The position of the robot is estimated using a bilateration method, while its orientation calculation utilizes tools from projective geometry. The validity and feasibility
of the approach are demonstrated through experiments.
| Original language | English |
|---|---|
| Title of host publication | 2019 7th International Conference on Future Internet of Things and Cloud Workshops (FiCloudW) |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Number of pages | 7 |
| ISBN (Electronic) | 978-1-7281-4411-5 |
| DOIs | |
| Publication status | Published - 02 Apr 2020 |