Robotic clusters: Multi-robot systems as computer clusters: A topological map merging demonstration
نویسندگان
چکیده
In most multi-robot systems, an individual robot is not capable to solve computationally hard problems due to lack of high processing power. This paper introduces the novel concept of robotic clusters to empower these systems in their problem solvings. A robotic cluster is a group of individual robots which are able to share their processing resources, therefore, the robots can solve difficult problems by using the processing units of other robots. The concept, requirements, characteristics and architecture of robotic clusters are explained and then the problem of “topological map merging” is considered as a case study to describe the details of the presented idea and to evaluate its functionality. Additionally, a new parallel algorithm for solving this problem is developed. The experimental results proved that the robotic clusters remarkably speedup computations in multi-robot systems. The proposed mechanism can be used in many other robotic applications and has potential to increase the performance of multi-robot systems especially for solving problems that need high processing resources.
منابع مشابه
Map-merging in Multi-robot Simultaneous Localization and Mapping Process Using Two Heterogeneous Ground Robots
In this article, a fast and reliable map-merging algorithm is proposed to produce a global two dimensional map of an indoor environment in a multi-robot simultaneous localization and mapping (SLAM) process. In SLAM process, to find its way in this environment, a robot should be able to determine its position relative to a map formed from its observations. To solve this complex problem, simultan...
متن کاملTopological Mapping with Multiple Visual Manifolds
We address the problem of building topological maps in visual space for robot navigation. The nodes of our topological maps consist of clusters along manifolds, and we propose an unsupervised learning algorithm that automatically constructs these manifolds the user need only specify the desired number of clusters and the minimum number of images per cluster. This spectral clustering like framew...
متن کاملREGION MERGING STRATEGY FOR BRAIN MRI SEGMENTATION USING DEMPSTER-SHAFER THEORY
Detection of brain tissues using magnetic resonance imaging (MRI) is an active and challenging research area in computational neuroscience. Brain MRI artifacts lead to an uncertainty in pixel values. Therefore, brain MRI segmentation is a complicated concern which is tackled by a novel data fusion approach. The proposed algorithm has two main steps. In the first step the brain MRI is divided to...
متن کاملDRAFT COPY: Topological Mapping with Multiple Visual Manifolds
We address the problem of building topological maps in visual space for robot navigation. The nodes of our topological maps consist of clusters in manifold space, and we propose an unsupervised learning algorithm that automatically constructs these manifolds the user need only specify the desired number of clusters and the minimum number of images per cluster. This spectral clustering like fram...
متن کاملRemotely-Processed Visual SLAM Using Open-Source Software
We developed a system that allows for the real-time data processing and command of a low-cost multi-robot setup that maps out an unknown environment. The objective is to localize the robot relative to its surroundings. To do so, we explore various robotic and computer vision techniques such as SLAM, network computing, map merging, and dense 3D reconstruction.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Robotics and Autonomous Systems
دوره 60 شماره
صفحات -
تاریخ انتشار 2012