Improvement flexibility of SLAM in unknown environment based on Robot Technology Middleware

In this paper, we presents an efficient simultaneous localization and mapping (SLAM) technique in multi-obstacle environment for indoor mobile robot navigation based on Laser Range Finder. We use Rao-Blackwellized Particle Filter (RBPF) to localize mobile robot and use Vector Field Histogram (VFH) for obstacle avoidance. In our system, Robot Technology Middleware (RTM) was used. By using RTM, we can develop functional elements as “RT software components” that can be implemented by different programming languages, run in different operating system, or connected in different networks to inter-operate. Based on RTM, we developed LRF data getting component, mobile robot control component, VFH component, RBPF component and GUI component. This paper describes the architecture of the proposed system and gives some experimental results.