Robust Artificial Intelligence Approach to Stabilize and Control Propeller Driven Hybrid UGV

Abstract

Hybrid Unmanned Ground Vehicle (HUGV) can drive on any terrain including walls and fly as well, using the multi directional thrust force of propellers. In the era of industrial revolution, hybrid UGVs need to be autonomous with intelligent decision making capabilities. During wall climbing of hybrid UGVs, stability is essential and depends on real time feedback from multiple sensors. To increase stability and control, it is proposed that PID control loops should be replaced by AI based algorithms that reduce the decision time and mathematical complexity. For autonomous movement in any terrain using the proposed model, intelligent UGVs can map and localize simultaneously.They can make intelligent decisions about mode of movement i.e. driving on ground or wall, steering on ground or wall, flying and maneuvering by using real time sensor readings. Integration of the proposed AI models with HUGV can be applied to many areas which are hard for humans to access, for instance; inspection of large structures, bio & nuclear hazard environments, planetary exploration & magnetic fields detection.