Abstract
For autonomous robots to deliver value in human centered environments, they must be able to autonomously open doors. For doing so, they have to overcome multiple challenges, one of which is, to estimate the desired door’s orientation and position. The information if the door handle is on the left or right side of the door must also be obtained.
In this work, a novel method, solving the stated problems is proposed. It’s perception is based on a sensor fusion of a monocular camera based state-of-the-art deep learning object detection algorithm with a 2D laser scan and subsequent line estimation. Additionally, a differential drive controller, using the
advancement of continuous goal pose updating, is proposed. During real-world experimentation with a differential drive robot, the implemented system was able to position the robot in front of a door every time with sufficient accuracy and is
thus found to solve the stated problem successfully.
In this work, a novel method, solving the stated problems is proposed. It’s perception is based on a sensor fusion of a monocular camera based state-of-the-art deep learning object detection algorithm with a 2D laser scan and subsequent line estimation. Additionally, a differential drive controller, using the
advancement of continuous goal pose updating, is proposed. During real-world experimentation with a differential drive robot, the implemented system was able to position the robot in front of a door every time with sufficient accuracy and is
thus found to solve the stated problem successfully.
| Original language | English |
|---|---|
| Title of host publication | PROCEEDINGS OF THE AUSTRIAN ROBOTICS WORKSHOP 2022 |
| Subtitle of host publication | Robotics for Assistance and in Healthcare |
| Place of Publication | Villach |
| Pages | 36-41 |
| Number of pages | 6 |
| ISBN (Electronic) | 978-3-99076-109-0 |
| Publication status | Published - 1 Jul 2022 |
