Subjective exploration for simultaneous localization and mapping used in ruins

According to the requirement of efficiency for rapid detection during the search and rescue in ruins, this paper proposes a subjective exploration strategy in the framework of simultaneous localization and mapping (SLAM). To balance the accuracy of SLAM algorithm and the efficiency of exploration, the problem of the subjective exploration of active SLAM is converted into an issue of multi-objective optimization. An objective function is presented to evaluate the uncertainties of estimation, the cost of movement and the gain of exploration. Furthermore, considering the uncertainty of estimation that is measured by the information entropy, an active constraint of loop closure is used for a backtracking correction of accumulated errors. Finally, the feasibility and validity of the proposed algorithm are verified by contrastive simulations and experiments.