System and Method for Probabilistic Multi-Robot Positioning

A method for estimating a pose of a robot, wherein the pose includes one or combination of a location of the robot and an orientation of the robot, wherein the method uses a processor coupled with stored instructions implementing the method, wherein the instructions, when executed by the processor carry out steps of the method, comprising:

• receiving sensor measurements of movements of the robot in an environment;
• executing iteratively a primary particle filter maintaining a set of primary particles and a secondary particle filter maintaining a set of secondary particles independently from each other to update the pose estimations in the primary and the secondary particles based on the sensor measurements, wherein each particle in the primary and secondary set of particles includes an estimation of a pose of the robot and a weight indicative of a probability of the pose estimation;
• receiving, in response to each encounter of the robot with a neighboring robot, neighboring particles of a particle filter of the neighboring robot identifying poses and likelihoods of the poses of the neighboring robot;
• replacing, in response to each encounter of the robot with the neighboring robot, the primary particles of the primary particle filter with the secondary particles fused with the neighboring particles;
• and
• outputting the pose of the robot according to the primary particles of the primary particle filter of the robot.

A non-transitory computer readable storage medium embodied thereon a program executable by a processor for performing a method, the method comprising:

• receiving sensor measurements of movements of the robot in an environment;
• execute iteratively a primary particle filter maintaining a set of primary particles and a secondary particle filter maintaining a set of secondary particles independently from each other to update the pose estimations in the primary and the secondary particles based on the sensor measurements, wherein each particle in the primary and secondary set of particles includes an estimation of a pose of the robot and a weight indicative of a probability of the pose estimation;
• receiving, in response to each encounter of the robot with a neighboring robot, neighboring particles of a particle filter of the neighboring robot identifying poses and likelihoods of the poses of the neighboring robot;
• replacing, in response to each encounter of the robot with the neighboring robot, the primary particles of the primary particle filter with the secondary particles fused with the neighboring particles;
• and
• outputting the pose of the robot according to the primary particles of the primary particle filter of the robot.