COOPERATIVE MAPPING AND LOCALIZATION OF AUTONOMOUS ROBOTS Principle

CO-OPERATIVE MAPPING AND LOCALIZATION OF AUTONOMOUS ROBOTS Principle Investigator: Lynton Dicks Supervisor: Karen Bradshaw

PRESENTATION OVERVIEW • Introduction • SLAM • CSLAM • History and Background • Hardware • Localization Algorithms • Map Merging

INTRODUCTION • Simultaneous Localization and Mapping (SLAM) • Co-operative Mapping and Localization (CSLAM) • Well researched for use on a single robot • Relatively new field • Benefits: • Uses: • Google Autonomous Vehicles • Navigate and map unreachable areas • Military Reconnaissance • Team work saves time • Improved Accuracy

SIMULTANEOUS LOCALIZATION AND MAPPING SLAM State Update Landmark Tracking (Dead reckoning) Pose Tracking Landmark Extraction Odometry Data Association

COOPERATIVE MAPPING AND LOCALIZATION • Each robots role • Master-slave • Independent Entities • Centralization / Convergence • Aggregation • Communication methods

HISTORY AND BACKGROUND Autonomous Robotic Programming Framework – Leslie Luyt 2009 • • • 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 A Robotic Framework for use in Simultaneous Localization and Mapping Algorithms – Shaun Egan 2010 • Generic Framework for both online and offline SLAM • Implemented SLAM for use with one robot

HARDWARE – FISCHERTECHNIK ROBOT • Two Encoder Motors • Two Ultrasonic Sensors • A Bluetooth Controller – 10 m range, ability to keep several connections alive at the same time

HARDWARE: ADDONS Motor Encoders Ultrasonic Sensors

TRIANGULAR BASED FUSION

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