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Adaptive real-time particle filters for robot localization
2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422)
Particle filters have recently been applied with great success to mobile robot localization. This success is mostly due to their simplicity and their ability to represent arbitrary, multi-modal densities over a robot's state space. The increased representational power, however, comes at the cost of higher computational complexity. In this paper we introduce adaptive real-time particle filters that greatly increase the performance of particle filters under limited computational resources. Our
doi:10.1109/robot.2003.1242022
dblp:conf/icra/KwokFM03
fatcat:7zsdxkw6bzehrewjg743yutiau