The investigations of the system which allow to avoid obstacles by the unmanned aerial vehicles (UAV) are presented in the paper. The system is designed to enable the full autonomous UAV flight in an unknown environment. As an information source about obstacles digital camera was used. Developed algorithm uses the existing relations between the imaging system and the parameters read from the UAV autopilot. Synthesis of the proposed obstacle avoidance control law was oriented for computational simplicity. Presented algorithm was checked during simulation studies and in-flight tests.
The necessary hardware and stereovision obstacle avoidance algorithm used by UAV (unmanned aerial vehicles) are described in this paper. The algorithm bases on method of matching the areas of image by using the standard SAD (sum of absolute differences) as a measure of fit. The rapid machining of the image is done by compare the windows areas. Method didn't check individual pixels what is important feature. The application target is operating in unknown environment with the changing light conditions which may disturb the proper operation of the obstacle avoidance algorithm. To reduce the reflection effect the averaging filter for each frame image is applied. This is realized by compare of the average brightness values in successive video frames. It allows to control the factor of the achromatic color in the image. To increase the performance, in the anti-collision system the algorithm controls only the area being the center of the picture connected with the direction of the UAV flight. When the obstacle is detected the image is tested globally to find the direction of the avoidance maneuver. Onboard computer for anti-collision system uses a serial communication with the autopilot ArdupilotMega. A quadrocopter (multicopter that is propelled by four rotors) was chosen as a control object.
The investigations of systems which allow to avoid obstacles by the unmanned aerial vehicles (UAV) are presented in the paper. The systems are designed to enable the full autonomous UAV flight in unknown, dynamic environment. Presented solutions enable to real-time control of the image brightness, without significantly disturbing the objectivity of the vision system. Single board ADSP-BF537 computer with built-in CMOS camera was used in the experimental studies. The final stage of the task is to perform fully autonomous missions of flying object with the real obstacles on its trajectory.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.