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Seminar Information

Title: Grid-based SLAM using Distributed Particles
Optimal and Robust Distributed Data Fusion for Joint Target-Detection and Tracking
Date: Thu 11 Jun 2009
Time: 11:00
Location: EM G19-20
Speaker: Shanker Keshav Das
Navid Bazzazzadeh
Vibot Master students
Description: Grid-based SLAM using Distributed Particles

This presentation attempts to identify a promising approach to the SLAM problem, a problem that has existed in some form or the other for nearly 20 years. In doing so, it uncovers a novel approach with an efficient memory implementation, using the most modern form of map representation and giving good results. It also shows much promise as a good framework for the development of better versions and is a strong contender for the position of popular SLAM approaches. It is based on the Particle Fitering technique, which is an emerging and highly researched method at the moment, and is known as Distributed Particle or DP SLAM. The dissertation will give a history of the SLAM approaches culminating in the chosen one and give reasons and explanations of the method. Tests, both new and old are presented and clear directions for future developments are proposed.


Optimal and Robust Distributed Data Fusion for Joint Target-Detection and Tracking

Generalising the single target tracking problem to multi-target tracking problem by using Random Finite Set theory and also applying optimal and robust data fusion techniques to fuse obtained information from two sensors.

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