Inferring a probability distribution function for the pose of a sensor network using a mobile robot
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Distributed collaborative localization of multiple vehicles from relative pose measurements
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Interrobot transformations in 3-D
IEEE Transactions on Robotics
Distributed consensus algorithms for merging feature-based maps with limited communication
Robotics and Autonomous Systems
Journal of Intelligent and Robotic Systems
Mutual localization in multi-robot systems using anonymous relative measurements
International Journal of Robotics Research
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In this paper, we address the problem of determining the 2-D relative pose of pairs of communicating robots from (1) robot-to-robot distance measurements and (2) displacement estimates expressed in each robot's reference frame. Specifically, we prove that for nonsingular configurations, the minimum number of distance measurements required for determining all six possible solutions for the 3 degree-of-freedom (3-DOF) robot-to-robot transformation is 3. Additionally, we show that given four distance measurements, the maximum number of solutions is 4, while five distance measurements are sufficient for uniquely determining the robot-to-robot transformation. Furthermore, we present an efficient algorithm for computing the unique solution in closed form and describe an iterative least-squares process for improving its accuracy. Finally, we derive necessary and sufficient observability conditions based on Lie derivatives and evaluate the performance of the proposed estimation algorithms both in simulation and via experiments.