• Corpus ID: 12089723

Mobile robot navigation with the use of semantic map constructed from 3D laser range scans

@article{Siemitkowska2011MobileRN,
  title={Mobile robot navigation with the use of semantic map constructed from 3D laser range scans},
  author={Barbara Siemiątkowska and Jacek Szklarski and Michal Gnatowski},
  journal={Control and Cybernetics},
  year={2011},
  volume={40},
  pages={437-453}
}
We describe a system allowing a mobile robot equipped with a 3D laser range finder to navigate in the indoor and outdoor environment. A global map of the environment is constructed, and the particle filter algorithm is used in order to accurately determine the position of the robot. Based on data from the laser only, the robot is able to recognize certain classes of objects like a floor, a door, a washbasin, or a wastebasket, and places like corridors or rooms. For complex objects, the… 

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References

SHOWING 1-10 OF 55 REFERENCES

Towards Semantic Navigation in Mobile Robotics

TLDR
The aim of this research is to develop a system that will enable a mobile robot to operate in a building with ability to recognise and identify objects of certain classes, including a 3D-model of the environment updated on-line, rule-based and feature-based classifiers of objects, a path planner utilizing cellular networks and other advanced tools.

Sonar-Based Real-World Mapping and Navigation

A sonar-based mapping and navigation system developed for an autonomous mobile robot operating in unknown and unstructured environments is described. The system uses sonar range data to build a

High resolution maps from wide angle sonar

TLDR
The use of multiple wide-angle sonar range measurements to map the surroundings of an autonomous mobile robot deals effectively with clutter, and can be used for motion planning and for extended landmark recognition.

Accurate object localization in 3D laser range scans

TLDR
A novel method for object detection and classification in 3D laser range data that is acquired by an autonomous mobile robot and using an Ada Boost learning procedure that enables highly accurate, fast and reliable 3D object localization with point matching.

Extraction of Semantic Information from the 3D Laser Range Finder

TLDR
A system for extracting semantic information in indoor and outdoor environment from 3D laser scanner is presented, using H aar-like features and Cellular Neural Networks to distinguish between different types of ground on which the robot is able to operate.

Real-time multi-robot path planner based on a heuristic approach

  • H. ChuH. ElMaraghy
  • Business
    Proceedings 1992 IEEE International Conference on Robotics and Automation
  • 1992
TLDR
A real-time approach to solve the trajectory planning problem using the latest feedback of robot joint locations from robot controllers and finds that even when the robot speed was varied from 25% to 80% of its full capacity, a collision-free path was found for each robot.

EKF-based 3D SLAM for structured environment reconstruction

TLDR
The extension and experimental validation of the widely used EKF-based SLAM algorithm to 3D space is presented and the probabilistic feature extraction method is described, capable of robustly extracting (infinite) planes from structured environments.

Automatic Classification of Objects in 3D Laser Range Scans

TLDR
A new method for object detection and classification in 3D laser range data that is acquired by an autonomous mobile robot is presented, which combines recent results in computer vision with the emerging technology of3D laser scanners.

Monte Carlo Localization: Efficient Position Estimation for Mobile Robots

TLDR
Monte Carlo Localization is a version of Markov localization, a family of probabilistic approaches that have recently been applied with great practical success and yields improved accuracy while requiring an order of magnitude less computation when compared to previous approaches.
...