Predicting the Performance of Cooperative Simultaneous Localization and Mapping (C-SLAM)
International Journal of Robotics Research
Scheduling Kalman filters in continuous time
ACC'09 Proceedings of the 2009 conference on American Control Conference
Cooperative multi-robot localization under communication constraints
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Interrobot transformations in 3-D
IEEE Transactions on Robotics
On the Network Coverage Intensity in the Presence of Clock Asynchrony
Wireless Personal Communications: An International Journal
International Journal of Robotics Research
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This paper addresses the problem of resource allocation in formations of mobile robots localizing as a group. Each robot receives measurements from various sensors that provide relative (robot-to-robot) and absolute positioning information. Constraints on the sensors' bandwidth, as well as communication and processing requirements, limit the number of measurements that are available or can be processed at each time step. The localization uncertainty of the group, determined by the covariance matrix of the equivalent continuous-time system at steady state, is expressed as a function of the sensor measurements' frequencies. The trace of the weighted covariance matrix is selected as the optimization criterion, under linear constraints on the measuring frequency of each sensor and the cumulative rate of the extended Kalman filter updates. This formulation leads to a convex optimization problem (semidefinite program) whose solution provides the sensing frequencies, for each sensor on every robot, required in order to maximize the positioning accuracy of the group. Simulation and experimental results are presented that demonstrate the applicability of this method and provide insight into the properties of the resource-constrained cooperative localization problem