Abstract:Abstract. Safe and optimal path planning in a cluttered changing environment for agents' movement is an area of research, which needs further investigations. The existing methods are able to generated secure trajectories, but they are not efficient enough to learn from their mistakes, especially when dynamics of the environment are concerned. This paper presents an advanced version of the Ant-Air algorithm, which can detect the changed scenario and while keeping the lessons learnt from the previously planned s… Show more
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