Estimating uncertain spatial relationships in robotics
Autonomous robot vehicles
FastSLAM: a factored solution to the simultaneous localization and mapping problem
Eighteenth national conference on Artificial intelligence
A frontier-based approach for autonomous exploration
CIRA '97 Proceedings of the 1997 IEEE International Symposium on Computational Intelligence in Robotics and Automation
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This paper investigates the on-line autonomous distribution for landmarks and the active exploration in environment without or lack of landmarks/features, such as disaster conditions and polar region. In such situation, the robot enters the environment carrying some landmarks and distributes them according to the rules given in this paper. The utility of the landmark distribution is analyzed. Then, based on the extended Kalman filter (EKF), the active exploration is converted into a problem of multi-objective optimization, in which the objective function includes three aspects, i.e. the accuracy of localization and mapping, the predictive area of the unknown environment that will be explored in next step and the information gain provided by the distributed landmarks respectively. The robot chooses the control input that optimizes the objective function such that accurate localization, high-quality mapping and complete exploration will be realized. And then, the supplementation and the redundancy elimination for landmarks are implemented. At last, a set of simulations is presented to show the effectiveness of our approach.