Vision-based Guidance and Navigation for Autonomous MAV in Indoor Environment
IR@CEERI: CSIR-Central Electronics Engineering Research Institute, Pilani
View Archive Info| Field | Value | |
| Title |
Vision-based Guidance and Navigation for Autonomous MAV in Indoor Environment
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| Creator |
Irfan, M
Dalai, S Kishore, K Singh, S Akbar, SA |
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| Subject |
Digital Systems
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| Description |
The paper presents an autonomous vision-based guidance and mapping algorithm for navigation of drones in a GPS-denied environment. We propose a novel algorithm that
accurately uses OpenCV ArUco markers as a reference for path detection and guidance using a stereo camera. It enables the drone to navigate and map an environment using vision-based path planning. Special attention has been given towards the robustness of guidance and controlling strategy, accuracy in the vehicle pose estimation and real-time operation. The proposed algorithm is evaluated in a 3D simulated environment using ROS and Gazebo. The results have been presented for drone navigation in a maze pattern indoor scenario. Evaluation of the given guidance system in the simulated environment suggests that the proposed system can be used for generating a 2D/3D occupancy grid map autonomously without the use of high-level algorithms and expensive sensors such as lidars.
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| Date |
2020
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| Type |
Conference or Workshop Item
PeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://ceeri.csircentral.net/554/1/032020.pdf
Irfan, M and Dalai, S and Kishore, K and Singh, S and Akbar, SA (2020) Vision-based Guidance and Navigation for Autonomous MAV in Indoor Environment. In: 11th International Conference on Computing, Communication and Networking Technologies (ICCCNT-2020), July 1-3, 2020, IIT Kharagpur, India. |
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| Relation |
http://ceeri.csircentral.net/554/
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