Intelligent and Autonomous UAVs

using Multi-Agent Systems

Seminários de Sistemas Inteligentes, Interacção e Multimédia

Prof. Rosaldo Rossetti Lúcio Sanchez PassosZafeiris Kokkinogenis Gustavo OliveiraRúben Veloso

Outline

Part I – Introduction

Part II – Related Works

Part III – Overall Architecture

Part IV – The Proposed Approach

Part V – Research Schedule

Part VI – Possible Projects

Introduction

Part I

Research ScopeU

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UUVs

UGVs

UAVsSymbioticSimulation

Design & Analysis

Decision-making

USVs

Research Problem

Proliferation of UAV’s in civil applications to substitute human in hazardous situations

The efforts of the research community unfold in different directions. Among them:• Autonomy in taking actions• Higher level of reasoning• Coordination of multiple units toward to a common goal• Embedded agent architectures• Improved control schemes• Localization and mapping under constrained of

computational resources

This work focuses on the first 4

Motivation and Research Aim

Our motivations• Multi-Agent system are used in the robotic field • Usually UAV for outdoor applications doesn’t manifest

high degree of decision-making capabilities• Existing UAV application (indoor) use expensive

infrastructures• Lack of a framework that supports the development of

agents for aerial robots

Main goal of the proposed research isto specify, devise and implement a quadcopter framework

featuring the necessary mechanisms to develop agents in a higher level that can be tested in real and virtual scenarios.

Similar Projects

Part II

Civil Applications

Figure 1: ptti.ipn.pt/news_items/7Figure 2: www.bbc.co.uk/news/business-21432170Figure 3: penngazetteblog.com/2011/01

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3

Quadcopters Occasional Projects

Name Entity Advantages Disadvantages

OS4 EPFL•Many controller options;•Highly detailed dynamics model;

•No autonomous flight;•Expensive;

N/A DTIC•Low cost;•Testbed for research;

•No OS on-board;•No autonomous flight;

N/A MIT•Virtual simulation;•Stabilization recovery;

•No autonomous flight;•Does not support 6 degrees of freedom;

MicroraptorOakland

University

•Camera;•Some degree of autonomy;

•Uses too many sensors;•Autonomy dependent on GPS signal;

RAVE ESTIA LIPSI •Tracking algorithm;•Gas powered;•No real autonomy;

N/AStandfordUniversity

•Ability to perform aggressive maneuvers;

•No autonomous flight;

Quadcopters Recurring Projects

FMA at Zurich Institute of Technology Google IO 2012, a quadcopter trio

throwing and catching a ball during the talk.

GRASP Lab at UPennYouTube clip showing a

quadcopter doing aggressive and acrobatic manoeuvres.

Overall Architecture

Part III

Overall Architecture

Physical System

Part IV

Physical Architecture

Conceptual Architecture

Conceptual Architecture

Why the OpenPilot CC3D?

OpenPilot Features

Our motivations• Agents are being used in the robotic field

• Lack of a framework that supports the development of agents for aerial robots

Main goal of the proposed research isto specify, devise and implement a quadcopter framework

featuring the necessary mechanisms to develop agents in a higher level that can be tested in real and virtual scenarios.

Robotic Operating System (ROS)

ROS is a flexible framework for writing robot software• Communications Infrastructure publish/subscribe anonymous message passing recording and playback of messages request/response remote procedure calls distributed parameter system

• Robot-Specific Features Robot Description Language Diagnostics Pose Estimation, Localization, Mapping, Navigation

• Tools Command Line / GUI rviz rqt

Simulator System

Part V

Simulator Architecture

Conceptual Architecture

Simulador

Quadcopter Virtual

Comunicação

UAVtalk

Ligação

Simbiótica

Ambiente

Quadcopters Occasional Projects

Simulators ofUAVs

Mixed RealitySimulators

Co-simulators

Flight Simulation USARSim JOCosim

SPEEDES Webots OFFIS SimLink

Virtual RealityToolbox

Microsoft RoboticsStudio simulator

TTMC

Piccolo Gazebo IntelWheels(LIACC/FEUP)

Microsoft FlightSimulator

X-Plane

FlightGear

Architecture

To specify, design and test e simulation platform to support the design and development of autonomous quadcopters

Lack of platforms for modeling and simulation of realistic 3d environments for multiple teams of quadcopters

Lack of platform that integrate a real system with a simulated one in a trasparent way

The associated cost for the implementation of real quadcopters is too high. A validate model of a quadcopter can help dvelopers implementtheir quad-based application in a safe environment.

Through the simulation platform we can control more than onequadcopters without human intervantion

Implementation of cordination/cooperation strategies for quadcopterteams in civil application scenarios can be performed and tested withouta great amount of founds.

Architecture

This project considers the design of applications in the civil domain

It specifies a quadcopter’s meta-architecture

It specifies the physics of the environment

It implements a simulation platform

It specifies a communication protocol

It specifies and implements the mechanisms for symbiotic simulation

Prototype

Jason/AgentSpeak platform

• AgentSpeak is an agent-oriented logic-based languageused to program multi-agent systems and complex agentbehaviour.

• Jason is an open-source java-based interpreter for anextended version of the AgentSpeak

• Jason/agentspeak offers the possibility to programcomplex behaviour with high-level abstractions

J3M features

MonkeyEngine is a java-based 3D game engine

• Free, open-source software

• Minimal adaptations for cross-compatibility

• Built around a shader-based architecture

• jMonkeyEngine SDK

• Complete and modular

• Bullet, a Java port of the Bullet Physics library

• Supports multiple Formats

Possible Projects

Part VI

Real Component

Apply operational research and machine learningapproach to tune the PID control in real time;

Integrate IR and sonar sensor to the actual control;

Implement a communication module with mobile devices for monitoring and control;

Implement a communication module between UAVs

Implement SLAM approach

Implement embedded agent to control the UAV

Virtual Component

Development of coordination/cooperationmechanism for solving complex tasks

Implement a proper ontology and a communication protocol.

Implement a more detailed model of theQuadcopter

Implement other autonomous vehicles in thesimulator

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Thank You!