Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Communications of the ACM - Robots: intelligence, versatility, adaptivity
The bits and flops of the n-hop multilateration primitive for node localization problems
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Localization from mere connectivity
Proceedings of the 4th ACM international symposium on Mobile ad hoc networking & computing
Simultaneous localization, calibration, and tracking in an ad hoc sensor network
Proceedings of the 5th international conference on Information processing in sensor networks
Distributed localization of networked cameras
Proceedings of the 5th international conference on Information processing in sensor networks
Robust message-passing for statistical inference in sensor networks
Proceedings of the 6th international conference on Information processing in sensor networks
Multi-robot Simultaneous Localization and Mapping using Particle Filters
International Journal of Robotics Research
Understanding the prediction gap in multi-hop localization
Understanding the prediction gap in multi-hop localization
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Localization system for mobile robot using wireless communication with IR landmark
Proceedings of the 1st international conference on Robot communication and coordination
Nonparametric belief propagation
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Range-Based localization in mobile sensor networks
EWSN'06 Proceedings of the Third European conference on Wireless Sensor Networks
Nonparametric belief propagation for self-localization of sensor networks
IEEE Journal on Selected Areas in Communications
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We consider the problem of tracking multiple moving robots using noisy sensing of inter-robot and interbeacon distances. Sensing is local: there are three fixed beacons at known locations, so distance and position estimates propagate across multiple robots. We show that the technique of Nonparametric Belief Propagation (NBP), a graph-based generalization of particle filtering, can address this problem and model multi-modal and ring-shaped uncertainty distributions. NBP provides the basis for distributed algorithms in which messages are exchanged between local neighbors. Generalizing previous approaches to localization in static sensor networks, we improve efficiency and accuracy by using a dynamics model for temporal tracking. We compare the NBP dynamic tracking algorithm with SMCL+R, a sequential Monte Carlo algorithm [1]. Whereas NBP currently requires more computation, it converges in more cases and provides estimates that are 3 to 4 times more accurate. NBP also facilitates probabilistic models of sensor accuracy and network connectivity.