lunabotics navigation package
DESCRIPTION
Lunabotics Navigation Package. Team May14-20 Advisor: Dr. Koray Celik Clients: ISU Lunabotics Club, Vermeer Company. Project Scope. NASA Lunabotics Mining Competition For university-level students to design and build a mining robot that can traverse the simulated Martian chaotic terrain - PowerPoint PPT PresentationTRANSCRIPT
Lunabotics Navigation PackageTeam May14-20Advisor: Dr. Koray CelikClients: ISU Lunabotics Club, Vermeer Company
Project Scope
NASA Lunabotics
Mining Competition• For university-level students
to design and build a mining robot that can traverse the simulated Martian chaotic terrain
• Points are awarded for autonomy
• Landmarks allowed for navigation
Project Scope
Our Clients
• Lunabotics Club
• Vermeer Companyo Large industrial
and agricultural equipment
Project Scope
ISU Lunabotics Club• Bump detectors
• Laser detector for orientation
• No obstacle detection
• LabView
Project Scope
Our Solution• Create prototype navigation system using computer vision techniques for
navigation and object detection
• Microsoft Kinect for prototype hardware solution
• Open-source software
Design
Platform• Laptop Computer
o 2.26 GHz Dual Core Processor
o 4 GB RAM
• Microsoft Kinecto RGB Camerao Infrared Optics
• Robot ‘Virgil’
Design
Virgil• Built by Dr. Koray Celik
• Representative of Lunabotics robot
• Modified Kinect
• Motor Controllero 4 Motors
• Encoder Controllero 6 Encoders
• Li-Ion Battery Powered
Design
Software• Ubuntu Linux 12.04 LTS
• OpenCV 2.4.8
• OpenNI 1.5.7.10
• PropulsionClass
Design
Design
Design
Landmark Detection• Acquisition Module
• Color Threshold
• Canny Convolution Operator
• Boundary Tracing
• Rectilinear Object Recognition
Landmark Detection
CannyThreshold
Landmark Detection
Contour All Poly Filter
Landmark Detection
● Unobtrusive landmark, not likely to be found naturally
● Searching for rectilinear shapes with overlapping midpoints
● State-space reduction to reduce noise
Design
Obstacle Detection• Acquire depth map
• Smoothing
• Regression
• Least Squares Plane Fitting
Obstacle Detection
• Plane Fitting
• Least Squares Regression
Smoothed Depth Mat
Normal Floor Plane
Blue - ObjectOrange - Floor
Obstacle Detection
• Threshold regression values
• Contour Filter
• Area of bounding rectangle
Path Generation
• Finite State Machine
• Landmark must be in sight upon start
• Drives towards landmark, avoids obstacles that appear in its path
• Maintains spacial awareness to landmark in case it loses sight
Path Gen
1. Find landmark
2. Move towards the landmark
3. Obstacle detected
4. Proceed on alternate path
5. Turn back to relocate landmark
6. Head to landmark
Accomplishments
Core Requirements
• Robot Movemento Smooth Acceleration and turningo Position and heading
• Landmark detectiono Recognize and distinguish between our two landmarks
• Obstacle detectiono Recognise obstacles above 4 cm tallo Recognize Landmarks as not obstacles
• Navigationo Obstacle avoidance
Challenges
• Landmark Detectiono Noise reduction
• Obstacle Detectiono Uneven terrain issues
• Encodero Set back by hardware (group is more software oriented
• OpenNI Bug o Appears around 3 minute marko Prevents code from scalability in terms of computational
complexityo Caused by XnSensorServer
Testing
Simulated Arena• 3 m X 2 m area
• Virgil is representative of Lunabotics Club’s Robot
Method• Test movement
• Test landmark detection, eliminate false-positives
• Test object detection
• Test obstacle avoidance
Demonstration
https://www.youtube.com/watch?v=WRIJiebZkOs
What’s Next?
• Introduce Improved Hardwareo 2.5-D Lidaro High Definition RGB Camera
• Integrate Encoder Support
• Improve Navigation Algorithm
Questions?