Abstract: A system for estimating a pose of a robot includes a particle filter to track the pose of the robot using particles that defining a probability of pose of the robot and a particle tuner to update the particles of the robot based on particles of neighboring robot. Upon receiving data indicative of relative pose between a pose of the robot and a pose of a neighboring robot, and particles of the neighboring robot, the particle tuner pairs an arbitrarily sampled particle of the robot with an arbitrarily sampled particle of the neighboring robot, determines a weight of the paired particles in reverse proportion to an error between a relative pose defined by the paired particles and the relative pose between the robot and the neighboring robot, and updates the particles of the robot in accordance to the weights of corresponding paired particles.

Abstract: A system for estimating a pose of a robot includes a particle filter to track the pose of the robot using particles that defining a probability of pose of the robot and a particle tuner to update the particles of the robot based on particles of neighboring robot. Upon receiving data indicative of relative pose between a pose of the robot and a pose of a neighboring robot, and particles of the neighboring robot, the particle tuner pairs an arbitrarily sampled particle of the robot with an arbitrarily sampled particle of the neighboring robot, determines a weight of the paired particles in reverse proportion to an error between a relative pose defined by the paired particles and the relative pose between the robot and the neighboring robot, and updates the particles of the robot in accordance to the weights of corresponding paired particles.