There are an ever growing number of aerospace applications demonstrating the effectiveness of emulating human decision making using fuzzy logic. Main research challenges include situational awareness and decision making in an uncertain, time-critical, spatio-temporal environment. In an effort to satisfy this demand, a MATLAB simulation of the classic arcade game PONG was utilized in conjunction with a fuzzy logic intelligence system that uses real-time reasoning and situational awareness, to emulate a single human player. In addition, a second simulation was created that incorporates an intelligent team of two players that use real-time collaboration and fuzzy reasoning and awareness capabilities to defeat the opposing team. For each simulation the paddles are capable of moving with two degrees of freedom, both translation (up and down) and rotation (clockwise and counter clockwise), to control the trajectory of the ball. By capitalizing on the opponent's inertia, location, and gaming strategy, the fuzzy logic paddles can react to the infinite number of interactive situations to defeat its challenger. After an iterative process of tuning the fuzzy system, both the singles and doubles games are proved difficult for human players to beat. This game is one of many practical examples of how fuzzy logic can be implemented into real life robotic applications.
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