Incremental multi-robot mapping

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.

Authors

• Rolf Lakaemper
• Longin Jan Latecki
• Diedrich Wolter

Keywords

• Shape
• Robot sensing systems
• Cognitive robotics
• Merging
• Simultaneous localization and mapping
• Stress
• Computational Intelligence Society
• Mathematics
• Informatics
• Process control
• Line Segment
• Global Map
• Part Of The Map
• Polyline
• Swarm Robotics
• Single Robot
• Geometric Process
• Similar Shape
• Complex Shapes
• Pose Estimation
• Pair Production
• Tangent Space
• Merging Process
• Hausdorff Distance
• Geometric Representation
• Iterative Closest Point
• Statistical Reasoning
• Loop Closure
• Error Problem
• Place Recognition
• Problem In Robotics
• Perceptual Grouping
• Mapping Problem
• Robot Pose
• Definition Of Cost
• Occupancy Grid
• 2D Point
• Reflection Point
• Point Scanning
• Robot Mapping
• Team of Robots
• Map Fusion
• Shape Similarity