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Validation of a PaCcET Socially-Aware Navigation Planner
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We present a socially aware navigation algorithm configured on a differential drive robot to validate simulation results. The robot will learn the social norms of four different scenarios, calculate a social goal trajectory, then follow the optimal path. A comparison between the normal navigation stack is presented as well as data comparing the time and position different between the experimentation and simulation results. Overall the robot performed efficiently in all four tasks and followed the expected behaviors such as respecting personal space.