Development of Simulink-based object detection program for a camera for micro-aerial vehicle
This paper presents research and development of our in-house object detection program for a digital camera that can be used in conjunction with a microprocessor on a micro aerial vehicle for autonomous flight in an indoor environment. The object detection program functions to create object boundaries and edges found in the video recorded by the camera. Thus creating boundaries of an environment. This work will use video and image analysis techniques to build colour co-relations and edges of the objects. The results from the analysis can then be passed to the microprocessor for processing. This then enables the micro aerial vehicle to be able to avoid and head towards objects in its surrounding autonomously. In our work, we also develop a 3D indoor navigation system, which is able to aid MAVs to safely navigate through the unknown and complicated indoor environment and complete autonomously necessary flight missions. The main tasks of this work involves hardware construction of an embedded navigation system (including multiple sensors, data and image processing units, and data and video links), the development and realization of robust 3D indoor navigation algorithms, and the tests of the system on the actual MAV platforms. In the navigation scheme, sophisticated machine vision algorithms such as robust feature extraction, an optical flow method and stereo vision approach are utilized to stabilize the MAVs and avoid the obstacles. The output of multiple sensors including inertial measurement sensors, visual sensors, and range sensors are employed to realize the 3D simultaneously localization and mapping (SLAM) for MAVs.
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