Robotic Delivery System with SLAM
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Transcript of Robotic Delivery System with SLAM
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Robotic Delivery System with SLAM
Blakely BoydKyle Elmer
Phillip Faber
Project Advisors: Dr. Aleksander Malinowski
Dr. In Soo Ahn
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RDS with SLAM
Outline• Inspiration and Introduction• Project Overview• Project Development
• Sensors• Mapping• Wi-Fi• Navigation
• Results• Future Recommendations• Questions
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RDS with SLAM
Introduction
• Autonomous delivery system
• Uses existing Wi-Fi access points
• Works from any laptop
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RDS with SLAM
Other Projects
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RDS with SLAM
Project Goals
• Wi-Fi signal strength acquisition• Robotic obstacle avoidance• Localization and mapping• Best path algorithm
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RDS with SLAM
Project Requirements
• Deliver within .5m of user• Detect and navigate openings .81m• Sensors range: .5 – 1m• Minimum three Wi-Fi routers
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RDS with SLAM
System Platform
• Pioneer p3dx• 44cm x 38cm x 22cm aluminum body
• Laptop interface•ARIA library
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RDS with SLAM
System Diagram
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RDS with SLAM
Project Division
• Phillip Faber• Sonar and IR Testing and Interfacing• Robot Navigation
• Kyle Elmer• Grid Mapping• Wi-Fi Data Filtering
• Blakely Boyd• Wi-Fi Navigation• Artificial Potential Field
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Wi-Fi Sender Wi-Fi Receiver
Potential Field Mapping and Navigation
Grid Mapping
IR Sensor Drivers
RDS with SLAM
Software Overview
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RDS with SLAM
Sonar Sensors
0 50 100 150 200 250 3000
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90 sensor 50 sensor 30 sensor
Samples
Distance
0 50 100 150 200 250 3000
1000
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90 sensor
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Distance
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RDS with SLAM
IR Sensors
• Sharp GP2Y0A02YK0F• 20cm to 150cm• 0 – 2.7V
• Sharp GP2D15• 24cm• “Touch-less Bump Sensors”
[1],[2]
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RDS with SLAM
IR Sensors
[1],[2]
Analog Sensor Digital Sensor
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RDS with SLAM
Interfacing
• Pico Tech USB ADC-11/10• USB• Open Source
• Sensor Class in Aria• 11 channel/10 bit
[3]
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Conversion
[3]
• Conversion from mV to mm
1.27 (2.096E-12 · x5 - 8.128E-9 · x4 + 9.827E-6 · x3 - .00182 · x2 - 4.130 · x + 2714.530)
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RDS with SLAM
Sensor Mount
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IR Sensor Testing
0 10 20 30 40 50 60 700
1000
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Sonar Sensors
S90S50S30
Samples
Dist
ance
(mm
)
0 10 20 30 40 50 60 700
1000
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IR Sensors
IR30IR60IR90
Samples
Dist
ance
(mm
)
0 10 20 30 40 50 60 700
1000
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IR and Sonar Sensors
S90S50S30IR30IR60IR90
Samples
Dist
ance
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)
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Wi-Fi Sender Wi-Fi Receiver
Potential Field Mapping and Navigation
Grid Mapping
IR Sensor Drivers
RDS with SLAM
Software Overview
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RDS with SLAM
Grid Mapping
• Used to: • Localize robot in the environment• Store specific Wi-Fi information• Find best path using potential field
• Multiple Approaches• Store full map in memory• Windowed map
• Windowed map is ideal
[4]
Status: ObstaclePotential: N/ANetworks:N/A
Status: ClearPotential: 13Networks:00:1C:DF:4D:20:0A 10000:1C:10:58:09:BA 6800:18:39:41:64:EB 6000:1B:11:66:E6:59 4900:18:39:58:4C:C4 47
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RDS with SLAM
Grid Mapping
• Initial mapping with obstacle detection
• Which grid square should be marked?
• x = cos(Ѳ) * (distance measured / grid size)• y = sin(Ѳ) * (distance measured / grid size)
• Ѳ = rotation of robot + angle of sensor
• Position in reference to robot
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RDS with SLAM
Grid Mapping
• Need to test using our sensor setup
• Simulator for P3Dx is ideal
• Needed to specify• Position of sensors (from center)• Angle of sensors
• Allows testing of all software components without robot
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RDS with SLAM
Grid Mapping• A simple grid map
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RDS with SLAM
Grid Mapping• A bit more complex…
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Wi-Fi Sender Wi-Fi Receiver
Potential Field Mapping and Navigation
Grid Mapping
IR Sensor Drivers
RDS with SLAM
Software Overview
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RDS with SLAM
Wi-Fi Sampling
• Software created in C#
• Utilizes NativeWifi.dll
• Tracks user specified MAC address
• Output gathered data to files for future manipulation
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RDS with SLAM
Wi-Fi Sampling
100 200 300 400 500 600 700 800 900 100055
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RAW
AVG
MED
Samples
Sig
nal Q
ualit
y
• Smoothing of Wi-Fi signal• Averaging• Median Filter
• Tested both techniques• Consistency• Transition• Reaction Time
• Using Averaging• 100 Samples• Smoother transitions
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RDS with SLAM
Wi-Fi Sender
• Measures local strength values
• Moving average
• User Datagram Protocol (UDP)
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RDS with SLAM
Wi-Fi Receiver
• Measures local strength values
• Initial mapping data
• Generates navigation
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Wi-Fi Sender Wi-Fi Receiver
Potential Field Mapping and Navigation
Grid Mapping
IR Sensor Drivers
RDS with SLAM
Software Overview
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RDS with SLAM
Localization
• Minimum three unique signals
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RDS with SLAM
Potential Field
• Artificial Potential Field
[5]
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RDS with SLAM
Potential Field
• Potential generated from goal
• Avoids local minima• Simple path creation
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RDS with SLAM
Results
• Simulator• Robot• Wi-Fi strength acquisition• Initial mapping• Potential field generation• Navigation of potential field
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RDS with SLAM
Results
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RDS with SLAM
Results
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RDS with SLAM
Final Hardware
Part Number Description Quantity Part Price Total
Pioneer p3dx Robotic Platform 1 $0.00 $0.00
Dell Laptop Project Computer 1 $0.00 $0.00
GP2Y0A02YK0F Analog Sensors 8 $12.50 $100.00
GP2D15 Digital Sensors 8 $12.50 $100.00
AD7224 DA Converter 1 $9.10 $9.10
USB ADC-11/10 USB AD Sensor Interface 1 $262.35 $262.35
Total 20 $471.45
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RDS with SLAM
Future Recommendations
• More robust navigation• Implement docking station• Port Sender program to mp3 player• Develop mechanism for getting objects• Implement IR sensors into ARIA library• Use with EE-SLAM• Use Wi-Fi software for other uses
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RDS with SLAM
Website
http://cegt201.bradley.edu/projects/proj2009/rdsslam/
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RDS with SLAM
Video
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RDS with SLAM
Thank you
• Project Advisors• Dr. Aleksander Malinowski• Dr. In Soo Ahn
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RDS with SLAM
Thank you
• Consultants• Dr. Joel Schipper• Mr. Steve Gutschlag• Mr. Nick Schmidt• Joe Buckner and Nir Chezrony
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RDS with SLAM
References
[1] Nourbakhsh, Illah R., and Roland Siegwart. Introduction to Autonomous Mobile Robots (Intelligent Robotics and Autonomous Agents.) London: The MIT Press, 2004 .
[2] Serrano, Oscar, Jose Marıa, Canas Vicente Matellan, andLuis Rodero. Universidad Rey Juan Carlos, 28933 Mostoles (Spain): 4 Dec. 2008<http://gsyc.es/jmplaza/papers/waf04.pdf>
[3] Lim, Chin-Heng, Yahong Wan, Boon-Poh Ng, and Chong-Meng Samson See. "A Real-Time Indoor WiFi Localization System Utilizing Smart Antennas." IEEE Transactions on Consumer Electronics 53 (2007): 618-622. 4 Dec. 2008 <http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=04266950>.
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References
[4] Sharp, GP2Y0A02YK0F Datasheet<http://www.acroname.com/robotics/parts/gp2y0a02_e.pdf>
[5]Sharp, GP2D12-15 Datasheet <http://www.acroname.com/robotics/parts/SharpGP2D12-15.pdf>
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RDS with SLAM
Picture References
[1] http://www.acroname.com/robotics/parts/R49-IR15.jpg
[2] http://www.acroname.com/robotics/parts/R144-GP2Y0A02YK.jpg
[3] http://images.picotech.com/adc11.jpg
[4] Nilsson, Nils. Artificial Intelligence: A New Synthesis. San Francisco, Calif: Morgan Kaufmann, 1998.
[5] Nourbakhsh, Illah R., and Roland Siegwart. Introduction to Autonomous Mobile Robots (Intelligent Robotics and Autonomous Agents.) London: The MIT Press, 2004 .
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Questions?