Abstract
A UAV equipped with an RGB-D camera and a downward facing optical flow sensor is set to explore an unknown indoor 3D-volume. The UAV’s visual odometry is accomplished through the fusion of IMU, depth readings and the optical flow sensor. While the UAV is moving using a skeletal path to avoid collisions between the surrounding obstacles, it computes features from the environment. These features assist the UAV to localize itself in a self-identified map using the RTAB-Map SLAM. The UAV moves to the fire-alike target-set and for the unexplored area it uses a Chebyshev shortest path from the boundary free cells to the boundary of the target-set. Due to SLAM-induced errors, the UAV employs virtual potential fields and local depth measurements for obstacle avoidance. Upon detection of the target, comprised as a fiducial marker to emulate a fire-source, the UAV uses a ballistic trajectory to propel its payload (fire extinguishing material) towards the target. Simulation studies using Unity for photo-realistic indoor imaging, Gazebo for the UAV dynamics and ROS as intermediate between these components is used to validate the suggested scheme.
Original language | English (US) |
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Article number | 54 |
Journal | Journal of Intelligent and Robotic Systems: Theory and Applications |
Volume | 108 |
Issue number | 3 |
DOIs | |
State | Published - Jul 2023 |
Keywords
- Chebyshev shortest path
- Indoor exploration
- RTAB-SLAM
- Skeletal path
- Unity
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Mechanical Engineering
- Industrial and Manufacturing Engineering
- Electrical and Electronic Engineering
- Artificial Intelligence