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Point Cloud Gathering for an Autonomous Bucket Excavator. Robotics Research Lab University of Kaiserslautern Gregor Zolynski. Overview. System for 3D data gathering from given sensor arrangement Introduction: machine and sensors Problems and limitations Concepts
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Point Cloud Gatheringfor an Autonomous Bucket Excavator Robotics Research Lab University of Kaiserslautern Gregor Zolynski
Overview System for 3D data gathering from given sensor arrangement • Introduction: machine and sensors • Problems and limitations • Concepts • Selected implementation details • Short example Point Cloud Gathering for an Autonomous Bucket Excavator
Active Scanners for Safety Applications 18t bucket excavator • Laser scanners on both sides of arm for safety • Panning: “natural” motion • utilize scanners for data gathering • no additional articulation necessary Point Cloud Gathering for an Autonomous Bucket Excavator
Laser Scanner & Scan Planes • Planar laser scanner(SICK LMS 151) • Coverage of 270° at 0.5° / 0.25° resolution • All scan points located on scan plane Point Cloud Gathering for an Autonomous Bucket Excavator
Laser Scanner & Scan Planes • Planar laser scanner(SICK LMS 151) • Coverage of 270° at 0.5° / 0.25° resolution • All scan points located on scan plane • Two scanners mounted vertically • Rotational encoder Point Cloud Gathering for an Autonomous Bucket Excavator
Problems Heavy noise Vibrations Undetected displacement Resulting system limitations Stationary vehicle Big objects Semi-dynamic terrain Dynamic/moving obstacles Problems, Limitations, … Point Cloud Gathering for an Autonomous Bucket Excavator
Problems Heavy noise Vibrations Undetected displacement Resulting system limitations Stationary vehicle Big objects Semi-dynamic terrain Dynamic/moving obstacles Desired Behavior Gather all data Maintain healthy resolution Remember briefly covered portions Quickly remove invalid data Problems, Limitations, Desired Behavior Point Cloud Gathering for an Autonomous Bucket Excavator
Concept: Data Gathering • Fuzzy points: Each point has a position and an uncertainty • Point cloud: New scan points added form each scan • Aging: Scan points “decay” and get discarded • Merging: New points are fused with close-by neighbors Point Cloud Gathering for an Autonomous Bucket Excavator
Concept: Data Gathering • Fuzzy points: Each point has a position and an uncertainty • Point cloud: New scan points added form each scan • Aging: Scan points “decay” and get discarded • Merging: New points are fused with close-by neighbors Point Cloud Gathering for an Autonomous Bucket Excavator
Sensor pose k Sensor pose k+1 Scan plane k+1 Concept: Deletion Volume • Volume spanned between two consecutive scans of each scanner • Usually combination of translation and rotation • Displacement is very small • Assumption: Space betweenscan planes is empty Delete all contained points Point Cloud Gathering for an Autonomous Bucket Excavator
Efficient Implementation • Deletion volume:4 planes + triangle strip • Naïve point-in-volume tests are expensive (20.000 points) • Faster: • Space binning • Signed distance to 4 planes • Intersection of ray from point towards sensor Point Cloud Gathering for an Autonomous Bucket Excavator
Quick Triangle Intersection • Scan points: polar coordinates(angle ~ point index) • Each point in point cloud in sensor’s coordinate space • Intersection candidate triangles:At least one corner above and below checked point • Quick text for min/max distance, then intersection Point Cloud Gathering for an Autonomous Bucket Excavator
Example Point Cloud Gathering for an Autonomous Bucket Excavator
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