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Restricted by environmental noise and the sensor itself performances, environmental information collected by various sensors of mobile robot has certain uncertainty. Laser Range Finder (LRF) has high precise measurement and large measuring range, but it can only acquire the environment information at a certain level, especially, it is unable to detect obstacles below the level of LRF measuring, so...
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...
Multi-robot system is widely used in exploring in large-scale unknown environment and performing the complex tasks. This paper presents map building for multi-robot system using RTM as communication platform. We use the Player Project works as simulation platform to realize topological map for multi-robotic system and use SP2ATM algorithm for path planning. The paper presents the architecture of the...
In this paper, an effective 3D map building approach based on range data from binocular stereo vision sensor and Laser Range Finder is introduced in detail. First of all, a local map temporal integration approach in which Bayesian filter based dynamic occupancy grid map modeling technique is employed to reasonably deal with measurement uncertainty involved in environment perception. In addition, as...
In this paper, we presents an efficient Simultaneous Localization and Map-Building (SLAM) technique for indoor mobile robot navigation based on Laser Range Finder and Rao-Blackwellized Particle Filter (RBPF). Robot Technology Middleware (RTM) was used in the developed system. By using RTM, we can develop functional elements as “RT software components” that can be implemented by different programming...
This paper presents a new method of localization and map building of mobile robot based on mixed map model using LRF (Laser Range Finder). The mixed model composed of occupancy grids and line character maps is utilized to represent the environment map. Firstly, the LRF models and Bayes rules are used to construct a local occupancy grid map. Then, we extract obstacles points to get a precise geometry...
As we all know that, SLAM (Simultaneous Localization and Mapping) are vital for mobile robot. This paper presents a method of map building using interactive GUI (Graphical User Interface) for an indoor service mobile robot because of the uncertainty of the sensors. What's more, the operator can modify the map compared with the real-time video from the web camera of the mobile robot. In the proposed...
As we all know that, it is vital to process environment data in map building of mobile robot. This paper presented two algorithms of map building using LRF for an indoor service mobile robot. Then we find their advantages and disadvantages, and the scope of application by comparing them in model and experiment in order to utilize effectively in practice. Experiments in indoor environment prove that...
This paper presents a method of map building using interactive GUI for an indoor service mobile robot. The reason we proposed this method is that it is difficult for a mobile robot to generate an accurate map although many kinds of sensors are used. In proposed system, the operator can modify map built by LRF and odometry, compared with the real-time video from web camera using modification tool in...
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