| Summary: | The Unmanned Aerial Vehicles (UAV) and its applications are growing for both civilian and military purposes. The operability of an UAV proved that some tasks and operations can be done easily and at a good cost-efficiency ratio. Nowadays, an UAV can perform autonomous tasks, by using waypoint mission navigation using a GPS sensor. These autonomous tasks are also called missions. It is very useful to certain UAV applications, such as meteorology, vigilance systems, agriculture, environment mapping and search and rescue operations. One of the biggest problems that an UAV faces is the possibility of collision with other objects in the flight area. This can cause damage to surrounding area structures, humans or the UAV itself. To avoid this, an algorithm was developed and implemented in order to prevent UAV collision with other objects. “Sense and Avoid” algorithm was developed as a system for UAVs to avoid objects in collision course. This algorithm uses a laser distance sensor called LiDAR (Light Detection and Ranging), to detect objects facing the UAV in mid-flights. This light sensor is connected to an on-board hardware, Pixhawk’s flight controller, which interfaces its communications with another hardware: Raspberry Pi. Communications between Ground Control Station or RC controller are made via Wi-Fi telemetry or Radio telemetry. “Sense and Avoid” algorithm has two different modes: “Brake” and “Avoid and Continue”. These modes operate in different controlling methods. “Brake” mode is used to prevent UAV collisions with objects when controlled by a human operator that is using a RC controller. “Avoid and Continue” mode works on UAV’s autonomous modes, avoiding collision with objects in sight and proceeding with the ongoing mission. In this dissertation, some tests were made in order to evaluate the “Sense and Avoid” algorithm’s overall performance. These tests were done in two different environments: A 3D simulated environment and a real outdoor environment. Both modes worked successfully on a simulated 3D environment, and “Brake” mode on a real outdoor, proving its concepts.
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