Principle Investigator: Lynton Dicks

Supervisor: Karen Bradshaw

CO-OPERATIVE MAPPING ANDLOCALIZATION OF AUTONOMOUS ROBOTS

• Introduction

• SLAM

• CSLAM

• History and Background

• Hardware

• Localization Algorithms

• Map Merging

PRESENTATION OVERVIEW

• Simultaneous Localization and Mapping (SLAM)

• Well researched for use on a single robot

• Uses:

• Google Autonomous Vehicles

• Navigate and map unreachable areas

• Military Reconnaissance

• Co-operative Mapping and Localization (CSLAM)

• Relatively new field

• Benefits:

• Team work saves time

• Improved Accuracy

INTRODUCTION

SIMULTANEOUS LOCALIZATION AND MAPPING

SLAM

State UpdateLandmark Tracking (Dead

reckoning)

Landmark Extraction

Data Association

Pose Tracking

Odometry

• Each robots role

• Master-slave

• Independent Entities

• Centralization / Convergence

• Aggregation

• Communication methods

COOPERATIVE MAPPING AND LOCALIZATION

• Generic Framework for both online and offline SLAM

• Implemented SLAM for use with one robot

• Generic Programming Framework to combine standard robotic operations with AI

• Abstracts away the details of interfacing and controlling robots

• Easy to implement new robot hardware classes to allow the framework to work with new hardware

HISTORY AND BACKGROUNDAutonomous Robotic Programming Framework – Leslie Luyt 2009

A Robotic Framework for use in Simultaneous Localization and Mapping Algorithms – Shaun Egan 2010

• Two Encoder Motors

• Two Ultrasonic Sensors

• A Bluetooth Controller – 10m range, ability to keep several connections alive at the same time

HARDWARE – FISCHERTECHNIK ROBOT

HARDWARE: ADDONS

Motor Encoders Ultrasonic Sensors

TRIANGULAR BASED FUSION

Sonar Wide Scan Arc TBF

LOCALIZATION ALGORITHMS• Constraints:

• Unique Landmark Associations and adequately spaced landmarks

• Time between observations

• Static Environment

• Limited to two robots

• The Algorithms

• Extended Kalman Filter

• Monte Carlo Particle Filter

MAP MERGING• Merge maps with observed robot

• Maps are transformed (rotated, translated) through merging algorithm

• Merging maps of populated environments by keeping track of moving objects

Questions?