Laser only feature based multi robot SLAM

This paper presents multi-robot simultaneous localization and mapping (SLAM) framework for a team of robots with unknown initial poses. The proposed solution is using feature based Rao-Blackwellised particle filter (RBPF) SLAM for each robot working in an unknown environment equipped only with 2D range sensor and communication module. To represent the environment in compact form, line and corner features (or point features) are used. By sharing and comparing distinct feature based maps of each robot, a global map with known poses is formed without any physical meeting among the robots. This approach can easily applicable to the distributed or centralized robotic systems with ease of data handling and reduced computational cost.