Incremental multi-robot mapping
Rolf Lakaemper,Longin Jan Latecki,Diedrich Wolter +2 more
- 05 Dec 2005
- pp 3846-3851
TL;DR: A new approach to merging robots' maps that is composed of a local geometric process of merging similar line segments (termed discrete segment evolution) with a global statistical control process is proposed.
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Abstract: The purpose of this paper is to present a technique to create a global map of robots' surroundings by converting the raw data acquired from a scanning sensor to a compact map composed of just a few generalized polylines (polygonal curves). We propose a new approach to merging robots' maps that is composed of a local geometric process of merging similar line segments (termed discrete segment evolution) with a global statistical control process. In the case of single robot, we are able to incrementally build a map showing the environment the robot has traveled through by merging its polygonal map with actual scans. In the case of a robot team, we are able to identify common parts of their partial maps and if common parts are present construct a joint map of the explored environment.
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Citations
Polygonal approximation of laser range data based on perceptual grouping and EM
Longin Jan Latecki,Rolf Lakaemper +1 more
- 15 May 2006
TL;DR: This work uses principles of perceptual grouping to evaluate the approximation quality obtained in each expectation maximization (EM) step, and is able to recognize a locally optimal solution, and modify the number of model components and their parameters.
31
Get me out of here: collaborative evacuation based on local knowledge
TL;DR: A novel paradigm for evacuation planning is suggested: decentralized planning based on sharing local knowledge, which is not only independent from infrastructure, and adapts to dynamic disasters, but also is as successful as centralized management in many scenarios.
27
Multi-robot simultaneous localization and mapping using D-SLAM framework
Zhan Wang,Shoudong Huang,Gamini Dissanayake +2 more
- 01 Dec 2007
TL;DR: An efficient algorithm to find the map overlap and corresponding beacons across the maps is developed from a point feature based medical image registration method and the joint compatibility test and shows valuable properties.
24
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Spatial Representation and Reasoning for Robot Mapping: A Shape-Based Approach
Diedrich Wolter
- 01 Jan 2008
TL;DR: A spatial representation based on shape information is proposed and shape analysis techniques are developed to tackle the correspondence problem in robot mapping.
22
Heterogeneous Map Merging: State of the Art
TL;DR: This research reviews the state of the art in homogeneous and heterogeneous map merging and illustrates the main research challenges in the area, including six factors that influence the outcome of map merging.
21
References
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M.W.M.G. Dissanayake,Paul Newman,S. Clark,Hugh Durrant-Whyte,M. Csorba +4 more
- 01 Jun 2001
TL;DR: The paper proves that a solution to the SLAM problem is indeed possible and discusses a number of key issues raised by the solution including suboptimal map-building algorithms and map management.
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Robotic mapping: a survey
Sebastian Thrun
- 01 Jan 2003
TL;DR: This article provides a comprehensive introduction into the field of robotic mapping, with a focus on indoor mapping, and describes and compares various probabilistic techniques, as they are presently being applied to a vast array of mobile robot mapping problems.
Robust registration of 2D and 3D point sets
Andrew Fitzgibbon
- 01 Jan 2001
TL;DR: A new method of registering point sets is introduced that is comparable in speed to the special-purpose Iterated Closest Point algorithm, and the registration error is directly minimized using general-purpose non-linear optimization (the Levenberg–Marquardt algorithm).
A Probabilistic On-Line Mapping Algorithm for Teams of Mobile Robots:
TL;DR: An efficient probabilistic algorithm for the concurrent mapping and localization problem that arises in mobile robotics is presented, which addresses the problem in which a team of robots builds a map on-line while simultaneously accommodating errors in the robots’ odometry.
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Probabilistic Algorithms in Robotics
TL;DR: It is proposed that the probabilistic approach to robotics scales better to complex real-world applications than approaches that ignore a robot's uncertainty.
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