Abstract
A mapping guidance algorithm of a quadrotor for unknown indoor environments is proposed. A sensor with limited sensing range is assumed to be mounted on the quadrotor to obtain object data points. With obtained data, the quadrotor computes velocity vector and yaw commands to move around the object while maintaining a safe distance. The magnitude of the velocity vector is also controlled to prevent a collision. The distance transform method is applied to establish dead-end situation logic as well as exploration completion logic. When a dead-end situation occurs, the guidance algorithm of the quadrotor is switched to a particular maneuver. The proposed maneuver enables the quadrotor not only to escape from the dead-end situation, but also to find undiscovered area to continue mapping. Various numerical simulations are performed to verify the performance of the proposed mapping guidance algorithm.
Highlights
Research on Unmanned Aerial Vehicles (UAVs) has been conducted in recent years due to the various applications [1,2,3,4,5]
As the quadrotor enters the dead-end phase II maneuver, the velocity vector command is adjusted to the direction which does not meet the pixel with zero value of distance transform image plane
Since the proposed guidance algorithm must be computed in real time, a designer should figure out the elements that can reduce the computational load of the embedded system while not affecting the mapping performance seriously
Summary
Research on Unmanned Aerial Vehicles (UAVs) has been conducted in recent years due to the various applications [1,2,3,4,5]. It is extremely risky to send humans into hazardous indoor structure without prior knowledge of the considered environment In this case, unmanned vehicles such as UAVs or mobile robots can be utilized to map and obtain three-dimensional data of the environment, instead of humans. Development of an indoor mapping guidance algorithm of the quadrotor with obtained object data points is necessary. The simulation results show that the proposed guidance algorithm maps indoor environments without a collision, and dead-end situations are appropriately handled. The contributions of this study are summarized as follows: first, a mapping guidance algorithm for an unknown indoor structure using a quadrotor is proposed. This method ensures both continuous mapping and collision avoidance.
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