DEVELOPMENT OF INTELLIGENT HYBRID ARCHITECTURE FOR AUTONOMOUS UAV

The technological innovation in robotics and in particular aerial vehicle drone-multirotor creates the need not only for advanced automation but also more autonomy, and even intelligence to develop innovative self-governance for decisions. This paper proposes an intelligent control architecture based on images processing technique for embedded self-enslavement in dynamic, uncertain and hostile environment with little or no human intervention. To provide UAV with capabilities of autonomous navigation in dynamic real world in uncertain or hostile environment robot control architecture is necessary. The challenge is to develop UAV control system obtaining intelligent suitable response of changing environment and adapt the software to the current situation. The Control architectures define how these abilities should be integrated to construct and develop an autonomous navigation with little or no human intervention. The objective is to estimate and maintain the accuratevalues of UAVs position and orientation. The onboard Inertial Measurement Unit (IMU) provide the measurements but it is mainly affected from the accumulated error due to drift in measurements. The Global Position System (GPS) measurements of vehicles position data can be fused with IMU measurements to compensate the accumulated error, But the GPS signals is not available everywhere and it will be degraded or fully not available in uncertain areas. This work proposes an intelligent control architecture based on images processing technique for embeddedself-enslavement in dynamic, uncertain and hostile environment with little or no human intervention.Our architecture is a family of intelligent control systems, hybrid and decomposed into flexible autonomous subsystems, its containing elements of sensory processing, world modeling, localization, Mission planning & high-level Expert system, and action processes to achieve or maintain its goals.