Robot Autonomous Exploration Planning Method and System Design
An improved autonomous exploration method is proposed to solve the problems of low efficiency,poor immediacy and repeated exploration of robots in unknown environments.Firstly,the local field of vision of the robot is optimized to solve the problem of incomplete map update when the obstacle information is missing.On this basis,taking the information gain of the frontier boundary point as the reward term and the moving cost as the penalty term,a nonlinear correction function is constructed to reason-ably select the boundary point.Finally,the simulation platform is built and the efficiency is improved.
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