drones:slam:start
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drones:slam:start [2023/09/17 13:04] – rolf.becker | drones:slam:start [2023/09/18 09:36] (current) – [Methods and Material] rolf.becker | ||
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====== Simultaneous Localization and Mapping (SLAM) for Indoor Navigation ====== | ====== Simultaneous Localization and Mapping (SLAM) for Indoor Navigation ====== | ||
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+ | Authors: [[https:// | ||
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+ | ===== Introduction ===== | ||
When we humans enter and discover an unknown environment we are implicitly performing SLAM. | When we humans enter and discover an unknown environment we are implicitly performing SLAM. | ||
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**SLAM in Robotics: | **SLAM in Robotics: | ||
This simplified behavioral model can be transferred to autonomous mobile robots. To make them really autonomous they have do do something link SLAM. It is a standard problem in robotics. | This simplified behavioral model can be transferred to autonomous mobile robots. To make them really autonomous they have do do something link SLAM. It is a standard problem in robotics. | ||
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+ | ===== Methods and Material ===== | ||
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**Flight Controller and Mission Control Computer: | **Flight Controller and Mission Control Computer: | ||
- | Our research assistant Harley Lara built the first flying robot (drone) in our team which is capable of SLAM. The flight attitude and stability of the drone is controlled by the standard open source flight controller PX4. This is responsible for the core functionality of the flying platform. It makes it flyable. The SLAM algorithm is run on a companion computer (here NVIDIA Jetson Xavier NX) which at the final stage of development will be responsible for the mission, i.e. the autonomous navigation, path decision as well as other higher level mission intention such as search and rescue (SAR) of people in disaster areas. This mission control computer tells the flight controller where to go. | + | Our research assistant Harley Lara built the first flying robot (aka drone) in our team which is capable of SLAM. The flight attitude and stability of the drone is controlled by the standard open source flight controller PX4. This is responsible for the core functionality of the flying platform. It makes it flyable. The SLAM algorithm is run on a companion computer (here NVIDIA Jetson Xavier NX) which at the final stage of development will be responsible for the mission, i.e. the autonomous navigation, path decision as well as other higher level mission intention such as search and rescue (SAR) of people in disaster areas. This mission control computer tells the flight controller where to go. |
- | **The Perception: | + | **Perception: |
- | In this first experiment we use a combination of two special cameras which cooperate closely: a tracking camera (Intel T265) and a depth camera (Intel D435i). They form the visual perception system. It allows to measure distances to " | + | In this first experiment we use a combination of two special cameras which cooperate closely: a tracking camera (Intel T265) and a depth camera (Intel D435i). They form the visual perception system. It allows to measure distances to " |
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+ | **" | ||
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+ | ===== Results ===== | ||
+ | The video shows the first experimental results. The top two video streams show two external observation cameras filming the drone flight in the university' | ||
- | The video shows the first experiment. | + | BTW: Video and audio are produced and cut by Harley, too. He also played |
drones/slam/start.1694948674.txt.gz · Last modified: 2023/09/17 13:04 by rolf.becker