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Title: Collision free path-planning for UAV flight near obstacles
Authors: Ng, Ee Meng
Keywords: DRNTU::Engineering::Mechanical engineering
Issue Date: 2018
Abstract: Improvements to flight controller units enable unmanned aerial vehicles(UAV) to follow a path set by the user with minimum deviation. This allows position-critical & timecritical missions to be carried out with ease. However, these paths are pre-planned and may be no longer valid as the when the UAV is carrying out the mission, due to changes in the environment and might cause the UAV to experience collision with new obstacles. To overcome this issue, a real-time obstacle detection-and-avoidance(DAA) framework is needed for the UAV for collision free flight near obstacles. In this research, we have constructed an obstacle detection-and-avoidance(DAA) framework for an autonomous UAV. The framework uses Moveit! Motion Planning library to perform real-time path planning & monitoring. The planned path will be sent to the flight control unit to be executed, and Moveit! will be used to monitor the path’s validity. If an obstacle is blocking the UAV, the Moveit! will perform re-planning to obtain a new collision-free path for the UAV. This enables the UAV to react to the presence of new obstacles and prevents it from colliding with them. The DAA framework is tested in a simulation and a real UAV. In the simulation, result shows that the framework is able to detect and determine whether an obstacle is obstructing the UAV. The framework will also be able to perform re-planning quickly. However, DAA in cluttered environment tend to be slow, due to the high amount of replanning and the long average re-planning time. In the real UAV test, result show that the framework is able to perform DAA similar to the simulation. However, presence of noise & disturbances from the environment reduces the reliability of the DAA framework.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:MAE Student Reports (FYP/IA/PA/PI)

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