Get all the updates for this publication
Conferences
Simultaneous Localization and Mapping of Mobile Robot using GMapping AlgorithmPublished in Institute of Electrical and Electronics Engineers Inc.
2020
Pages: 56 - 60
The main aspect of the mobile robot system is the ability to localize itself accurately and simultaneously, create an map of the unknown environment. Simultaneous localization and mapping (SLAM) is required for autonomous navigation. The framework of SLAM is based on Rao-Blackwellized Particle Filter (RBPF) that is applied through G-Mapping algorithm. The 2D LIDAR scanner and odometer is used as main sensor in the simulated robot model. The RBPF algorithm and the data of the LIDAR and odometer are fused to create the 2D map of the simulated environment as well as localization and navigation of the robot in unknown environment. Experiment Implementation is carried in Robotic Operating system (ROS) and gazebo simulator. © 2020 IEEE.
Content may be subject to copyright.
About the journal
| Journal | Data powered by TypesetProceedings - 2020 6th IEEE International Symposium on Smart Electronic Systems, iSES 2020 |
|---|---|
| Publisher | Data powered by TypesetInstitute of Electrical and Electronics Engineers Inc. |
Authors (3)
Saravanakumar D- Energy Efficiency Analysis of Interconnected Pneumatic Cylinders Servo Positioning System
- Sensor Integration-Based Approach for Automatic Fork Lift Trucks
- Application of failure mode and effect analysis in manufacturing industry - an integrated approach with FAHP-fuzzy TOPSIS and FAHP-fuzzy VIKOR
- Biomimetic Copper Complex Containing Polymer Modified Electrode for Electrocatalytic Reduction of Oxygen
Jegadeeshwaran R- Improved pose estimation by inlier refinement for visual odometry
- Brake fault diagnosis using Clonal Selection Classification Algorithm (CSCA) – A statistical learning approach
- Determination of minimum sample size for fault diagnosis of automobile hydraulic brake system using power analysis
- Vibration based Condition Monitoring of a Brake System using Statistical Features with Logit Boost and Simple Logistic Algorithm
Sakthivel G- A genetic algorithm-based artificial neural network model with TOPSIS approach to optimize the engine performance
- Selection of Optimum Fuel Blend in an Ic Engine Using Fahp-Promethee
- Comparative analysis of performance, emission and combustion parameters of diesel engine fuelled with ethyl ester of fish oil and its diesel blends
- Prediction of CI engine performance, emission and combustion characteristics using fish oil as a biodiesel at different injection timing using fuzzy logic
