LUNaR SECON I Senior Design I Midterm Presentation October 4, 2007

Team 1 Dr. Bryan Jones, Advisor Ted Copeland Bryan Reese Theresa Weisenberger Jeffrey Lorens Block DetectionXX Path DetectionXX Object AvoidanceXX CommunicationXX

Outline Competition Overview LUNaR Project Breakdown Technical Constraints Practical Constraints Summary

Competition: Summary Lunar mineral harvesting robot Color-coded blocks with RFID tags Collect maximum of four blocks and bring them back to home base Final rounds head-to- head

Competition: Court Home Bases Red/Blue/White Blocks X Black Blocks Pea Gravel Sand Paint 6 ft Symmetrical Block Placement IR Beacons (2.5kHz and 4 kHz) on Home Bases Note: Grid will not be on the field during competition X

Outline Competition Overview LUNaR Project Breakdown Technical Constraints Practical Constraints Summary

Project Management PathDetermination ObjectAvoidance BlockDetection BlockRetrieval BaseDetection Locomotion ReturnHome Team 1 Team 2

Team 1 Block Detection Color Detection Location Path Planning Shortest route Communicate Environmental sensing

Team 1 Object Avoidance Blocks Other robot Home Base Detection IR LEDs Correct Frequency

Outline Competition Overview LUNaR Project Breakdown Technical Constraints Practical Constraints Summary

Technical Constraints NameDescription Block Detection The robot must be able to detect and distinguish among red, blue, black, and white blocks. Path Planning The robot must find a path to a target block while avoiding any obstacles.

Block Detection Reasons for block detection and color differentiation Prioritize block pick up Minimize the time spent collecting blocks Approaches Blind Grid Search Range Finder Search Vision Processing Laser Range Finder

Blind Grid Search +Simplest approach +Must pick up all blocks –Cannot determine a block’s color –Blocks moved from their initial location will not be found

IR Range Finder Search +Little processing required +Not confused by colored floor –Cannot determine a block’s color –Small field of view RF

Vision Processing +Can determine a block’s color +Block retrieval can be prioritized +Wide field of view –Can be confused by the colored floor and changes in lighting –Lots of processing required

Laser Range Finder +Can determine a block’s color +Block retrieval can be prioritized +Wide field of view +No color confusion +Less complicated processing –Laser must be turned off and on [1]

Laser Range Finder Laser Beam on Blocks The laser point on a block

Environmental Sensing Calculating distance to walls Four IR rangefinders One on each side of the robot Placed at least 3” above the ground Calculate position on court by triangulation RF 3” RF

Distance Measurement The SHARP GP2Y0A02YK0F Emits IR beam with an IRED Dimensions: 1.16×0.5×0.85 in Range: ~ 8 – 60 in Output: Analog and digital models available [2]

Outputs a high or low voltage depending on the distance of the detected object. Targets do not have set distances –Would make rangefinding more difficult IR: Digital versus Analog Digital

IR: Digital versus Analog +Outputs a voltage that is proportional to the distance of the detected object. +Allows specific distance calculation Best option for this application Analog

Outline Competition Overview LUNaR Project Breakdown Technical Constraints Practical Constraints Summary

Practical Constraints TypeNameDescription SustainabilityDependability The robot must be sturdy enough to withstand repeated use. ManufacturabilityModularity The robot must be designed as a set of subsystems that can be replaced independent of other subsystems.

Sustainability Robot must be able to run full round (6 min) without repair. Rugged enough to sustain normal wear. Only minor maintenance (i.e. battery changing) between rounds

Manufacturability 10” x 10” x 11” size constraint [3] Built in a modular fashion Easy replacement of a failed subsystem Most accessible: battery packs

Outline Competition Overview LUNaR Project Breakdown Technical Constraints Practical Constraints Summary

Timeline SepOctNovDec Block Detection Path Planning Home base detection Integration Test/Debug Aug

Summary AspectMethod Block DetectionLaser Rangefinder Block RetrievalColor-sensing Camera Path Planning Block Detection + Environmental Sensing Practical Constraints Sustainability Modularity

References [1] Maxon, K. “A Real-time Laser Range Finding Vision System,” Encoder [Online]. Available: [2] SHARP. “SHARP GP2Y0A02YK0F.” SHARP Corporation, [Online]. Available: [3] Huntsville IEEE Section. "SoutheastCon 2008 Hardware Competition Rules: Return to the Moon," IEEE SoutheastCon Available: Questions?