simultaneous localization and mapping using zigbee protocol - project...

Simultaneous Localization and Mapping using ZigBeeProtocol

Project Proposal

Kyle Hevrdejs Jacob KnollAdvisor: Dr. Suruz Miah

Department of Electrical and Computer EngineeringBradley University

1501 W. Bradley AvenuePeoria, IL, 61625, USA

Tuesday, November 29, 2016

K. Hevrdejs,J. Knoll (Bradley University) SLAM using ZigBee Protocol (Proposal) November 29, 2016 1 / 35

http://www.bradley.edu

Outline

1 Introduction

2 Background Study

3 Functional RequirementsSpecifications

4 Preliminary ResultsSimulationDesignExperimental Activities

5 Parts List

6 Deliverables

7 Timeline and Milestones

8 Future Directions



IntroductionApplications

Warehouses

Cleaning systems

Robotic concierge

Large office mail systems

Mining

Research and education



Introduction

Problem Statement

Design and implementation of a low-cost localization and mapping systemusing off-the-shelf hardware components.



Background StudyLiterature

Most systems in research environments utilize RFID

Directional antennas with wireless sensor beacons

Using a parabolic reflector to estimate angle-of-arrival

Research literature showing proof of concept and not a real worldimplementation

Implemented on custom, purpose-built mobile robots



Background StudyChallenges

Accuracy of measurements, mapping, and localization

Improve signal-to-noise ratio (SNR)

Balancing cost and accuracy in the number of wireless beacons



Terminology

Pose: q = [x , y , θ]T

Root Mean Square Error: RMSE =√

1tf

∫ tf0 [e(t)]

2dt

Robot error: eP(t) =√

(x̂(t) − xd(t))2 + (ŷ(t) − yd(t))2

eB(t) = Σni=1ei (t) where

ei (t) =√

(x̂i (t) − xdi (t))2 + (ŷi (t) − ydi (t))2



Functional RequirementsSystem Architecture

Figure: System Architecture



Functional RequirementsSystem Architecture

(a) (b) (c)

Mobile robot (Pioneer 3-DX)

Interfaced using BeagleBone Black running Robot Operating System(ROS indigo1)

Ceiling mounted beacons (XBee modules)

Predefined waypoints (implemented in algorithm)1www.ros.org


http://www.bradley.eduwww.ros.org

Functional RequirementsSystem Block Diagram

Localizationand Mapping

Power (12 V)

Pre-definedwaypoints

Beacon's received signalstrength (RSS) and ID from beacon

Robot's estimatedpose

Beacons' estimatedposition

Robot's pathfollowing waypoints

Noise fromenvironment

Input Output

Figure: System block diagram



Functional RequirementsSubsystem Block Diagram

Controller PreprocessorMobile

Robot

Estimation

PredefinedWaypoints(desired)

XBee

Network

ν (linear velocity)

γ (steering angle)

ν (linear velocity)

! (angular velocity)

Noisy Robot Pose

BeaconIDs

Beacons' receivedsignal strength (RSS)

Noise fromenvironment

Robot's path

following way-

points

Estimated Position of XBees

Estimated Robot Pose

Estimated Robot Pose

Estimated Positionof XBees

Figure: Subsystem block diagram



Functional RequirementsSubsystem Block Diagram

Four subsystems

ControllerPreprocessorMobile RobotEstimation

Outputs are for debugging, used internally for implementingEKF-SLAM algorithm



Outline

1 Introduction

2 Background Study



5 Parts List

6 Deliverables


8 Future Directions



Functional RequirementsSpecifications

Cost under $500

Localize mobile robot with RMSE ≤ 30 cmEstimate beacon positions with RMSE ≤ 30 cmUse ROS



Outline

1 Introduction

2 Background Study



5 Parts List

6 Deliverables


8 Future Directions



Preliminary ResultsV-REP

Real-time robot simulator

Advantages

Simulates all dynamics of the robot (driving kinematics, object physics,sensors)Easy to use through a variety of programming languagesProvides real-time simulation data for use in algorithm



Preliminary ResultsSimulation Setup

Time step, T = 0.25 s

Linear velocity standard deviation, σν = 8.8858 × 10−4

Angular velocity standard deviation, σω = 0.0012

Observation range standard deviation, σR = 1

Observation bearing standard deviation, σB = 5◦

Maximum Pioneer linear velocity is 1.2 m s−1

Maximum Pioneer angular velocity is 300 ◦ s−1

Other parameters: 9 beacons, 2000 iterations, observations every 8iterations



Preliminary ResultsSimulation

Figure: Starting configuration of the V-REP simulation




0 200 400 600 800 1000 1200 1400 1600 1800 2000

Iteration

0

0.1

0.2

0.3

0.4

0.5

0.6

eP(t

) [m

]

Robot Error

Figure: Robot error from simulation over 2000 iterations with an RMSE of 0.0928




0 50 100 150 200 250

Observation

0.5

1

1.5

2

2.5

3

3.5

4

eB(t

) [m

]

Total Beacon Position error

Figure: Total beacon error from simulation over 250 observations with an RMSEof 1.7254



Outline

1 Introduction

2 Background Study



5 Parts List

6 Deliverables


8 Future Directions



Preliminary ResultsDesign

Pioneer 3-DXBeagleBone

BlackUART UARTXBee

Coordinator

XBee

End-Devices

ZigBee

Wireless

Network

Figure: System interfaces



Preliminary ResultsDesign

Basic wireless communication between two XBees in X-CTU, XBeeconfiguration software, running on a PC.

C program running on BeagleBone Black which interfaces with XBeevia UART for basic communication between two XBees.

Expanded C program with the help of open source library libxbee2 topacket-based communication.

Current functionality to obtain RSSI from beacons:

Robot mounted XBee (Coordinator) transmits ping signal to beacons.Beacons will register the RSSI.Coordinator then requests beacons (End-Devices) to return individualIDs and registered RSSI.

2https://github.com/attie/libxbee3K. Hevrdejs,J. Knoll (Bradley University) SLAM using ZigBee Protocol (Proposal) November 29, 2016 23 / 35

http://www.bradley.eduhttps://github.com/attie/libxbee3

Outline

1 Introduction

2 Background Study



5 Parts List

6 Deliverables


8 Future Directions



Preliminary ResultsExperimental Activities

Figure: Lab set up for experiments




0.5 1 1.5 2 2.5 3 3.5 4

Actual Distance [m]

-80

-75

-70

-65

-60

-55

-50

-45

-40

RS

SI [d

Bm

]

XBee RSSI Measurements

PL = 1

PL = 2

PL = 3

Figure: RSSI vs. Actual Distance




d = f (RSSI)

d = 10−RSSI−Pref

10η

where d is the calculated distance, RSSI is the measured RSSI, Pref is thepower level at a reference distance of 1 m, and η is the propagationconstant




0.5 1 1.5 2 2.5 3 3.5 4

Actual Distance [m]

0

0.5

1

1.5

2

2.5

3

Calc

ula

ted D

ista

nce [m

]

XBee Ranging Data

PL = 1

PL = 2

PL = 3

Figure: Calculated Distance vs. Actual Distance



Parts List

This list does not include parts already in the lab such as the Pioneer3-DX, wire, capacitors, or resistors. We were also fortunate enough tohave access to a BeagleBone Black and some XBee modules forexperimentation without having to place a parts request.

Part Price Quantity

XBee S2C w/ whip antenna $18.19 6

XBee Interface Board $5.31 6

Perforated Circuit Board $2.84 4

Stepper Motor $14.95 1

Motor Controller $19.95 1

3.3 V Regulator $0.79 10

9 V Battery Clip $0.39 10

Table: List of ordered parts



Deliverables

Experimental results

Report

Complete Documentation



Timeline and MilestonesFall Semester

2016

Sep Oct Nov Dec

100%Research100%Research XBee functionality

100%Research EKF-SLAM

100%Simulation100%Simulate using MATLAB

100%Simulate using V-REP

100%XBee Communication100%Communication with X-CTU

100%AT Commands

100%Remote AT Commands

100%XBee Library

100%Get XBee RSSI data from multiple beacons



Timeline and MilestonesSpring Semester

2017

Jan Feb Mar Apr May

100%XBee Communication100%Get XBee RSSI data from multiple beacons

0%Angle Estimation0%Build Reflector

0%Testing and Debugging

0%Subsystem Preparation0%Install ROS for Control of Pioneer 3-DX

0%Create ROS Node for Estimator Subsytem

0%Integration and Test0%Integrate subsystems

0%Test and Debug System

0%Project Completion Work



Future Directions

Estimate angle-of-arrival from wireless beacons

Complete subsystems

Integrate subsystems

Demonstrate completed system



References I

F. Martinelli, “A robot localization system combining rssi and phaseshift in uhf-rfid signals,” IEEE Transactions on Control SystemsTechnology, vol. 23, no. 5, pp. 1782–1796, Sept 2015.

E. DiGiampaolo and F. Martinelli, “Mobile robot localization using thephase of passive uhf rfid signals,” IEEE Transactions on IndustrialElectronics, vol. 61, no. 1, pp. 365–376, Jan 2014.

D. Song, C. Y. Kim, and J. Yi, “Simultaneous localization of multipleunknown and transient radio sources using a mobile robot,” IEEETransactions on Robotics, vol. 28, no. 3, pp. 668–680, June 2012.

D. Hahnel, W. Burgard, D. Fox, K. Fishkin, and M. Philipose,“Mapping and localization with rfid technology,” in Robotics andAutomation, 2004. Proceedings. ICRA ’04. 2004 IEEE InternationalConference on, vol. 1, April 2004, pp. 1015–1020 Vol.1.



References II

B. N. Hood and P. Barooah, “Estimating doa from radio-frequencyrssi measurements using an actuated reflector,” IEEE Sensors Journal,vol. 11, no. 2, pp. 413–417, Feb 2011.

V. Malyavej, W. Kumkeaw, and M. Aorpimai, “Indoor robotlocalization by rssi/imu sensor fusion,” in 2013 10th InternationalConference on Electrical Engineering/Electronics, Computer,Telecommunications and Information Technology, May 2013, pp. 1–6.



IntroductionBackground StudyFunctional RequirementsSpecifications

Preliminary ResultsSimulationDesignExperimental Activities

Parts ListDeliverablesTimeline and MilestonesFuture DirectionsAppendix

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