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WellManagedAsh

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laser scanning geoinformatics remote sensing

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Laserscanning – Modeling and Interpretation Claus Brenner (Lecture) Tim Schimansky (Exercises) Institute of Cartography and Geoinformatics Leibniz University Hannover Contents u Basic idea: § „Selected techniques and algorithms from low-, intermediate- and high-level...

Laserscanning – Modeling and Interpretation Claus Brenner (Lecture) Tim Schimansky (Exercises) Institute of Cartography and Geoinformatics Leibniz University Hannover Contents u Basic idea: § „Selected techniques and algorithms from low-, intermediate- and high-level processing of laser scan data § and the corresponding application areas“ u Topics § Laser scanning – basics & applications § Transformations and their estimation § Registration of datasets § Segmentation and feature extraction § Classification § Markov chain Monte Carlo and high-level reconstruction § Neural networks in laser scanning 2 Aerial Laserscanning Aerial Laserscanning 4 Example (TopoSys) 5 Example (TopoSys) 6 Example (TopoSys) 7 Example (TopoSys) 8 Example (TopoSys, orthoimage pixel = 0.4 x 0.4 m2) 9 Example: Hannover main station – point cloud 10 Example: Hannover main station – point cloud 11 Example: Hannover main station – regular raster 12 Example: Hannover main station – regular raster 13 Example: Optech ALTM (old) All images taken from www.optech.ca 14 Example: Optech ALTM (old) 15 All images taken from www.optech.ca Example: Teledyne Optech Galaxy (on gyro stabilization mount) 16 All images taken from www.teledyneoptech.com/en/products/airborne-survey/galaxy/ Example: Riegl VQ-1560 II Images taken from www.riegl.com 17 Example: Riegl VQ-1560 II Images taken from www.riegl.com 18 Example: IGI LiteMapper 19 Images taken from www.igi-systems.com/litemapper.html Example alternative mount: “wing pod” (Riegl VQX-1) Images taken from www.riegl.com 20 Example alternative mount: “wing pod” (Riegl VQX-1) Images taken from www.riegl.com 21 Example: helicopter Images taken from www.igi-systems.com/litemapper.html 22 Example (helicopter scan, approx. 40 points/m2) (Provided by ITC, The Netherlands) 23 Example (helicopter scan, approx. 40 points/m2) (Provided by ITC, The Netherlands) 24 Gyrocopter scanning Images taken from www.igi-systems.com/litemapper.html 25 Gyrocopter Image taken from www.igi-systems.com/litemapper.html 26 Other platforms: UAVs RIEGL VUX-240: RIEGL VUX-1UAV: RIEGL miniVUX-2UAV: 1,800,000 points/s, 4.1 kg 500,000 points/s, 3.5 kg 200,000 points/s, 1.55 kg (2 kg with IMU) (4.9 kg with IMU) 27 (Images source: riegl.com) Other platforms: UAVs Image source: aeroscout.ch 28 Other platforms: UAVs Images source: aeroscout.ch 29 Other platforms: UAVs Image source: aeroscout.ch 30 Comparison of acquisition characteristics System Cost per v_min/ v_max Min. distance, flight hour m/s [km/h] at 100 Hz Fixed wing aircraft 1100 €/h 40/110 [140/400] 0.4 m Helicopter 1500 €/h -/80 [-/290] Application specific Gyrocopter 500 €/h 20/40 [70/140] 0.2 m (Source: Jens Kremer, IGI) 31 Terrestrial laserscanning Terrestrial laser scanner systems u Active, non-triangulating 33 (image sources: Leica, Faro, Riegl, Z+F) Hybrid measurement systems u Systems consist of a laser- and optionally an image sensor § Integrated camera or § External camera, which is connected to the laser scanning unit (detachable) 34 (image sources: Z+F, Riegl) Terrestrial scan data Intensity Distance Color (from camera) 35 Terrestrial scan data 36 Comparison of image and scan data density Image data (0.03°) 3D scan points (0.12°) 37 37 Example scan (University main building “Welfenschloss”) 38 Example scan (University main building “Welfenschloss”) 39 Point cloud (Hannover opera, several scans) 40 Point cloud (Leineschloss, Hannover) 41 42 Mobile laser scanning LiDAR mobile mapping Mobile Mapping: Streetmapper @ ikg, Hannover 44 Mapping van: StreetMapper 4 terrestrial scanners (Riegl) www.streetmapper.net 45 Total scanned area + groundplans from cadastral map 46 Total scanned area 47 Königsworther Platz, scan data and trajectory 48 Example system: Optech Lynx § 2 scanners § 600 Hz (lines, per sensor) § 800 kHz (per sensor) § up to 4 echoes § 5 mm precision § 5.76 bn points per hour § Less expensive 1-head system available Image source: Optech/ Teledyne Optech 49 Example system: Riegl VMX-2HA u 2 scanners u 250 Hz (per sensor) u 1000 kHz (per sensor) u “unlimited” echoes (full WF) u 3 mm precision u 7.2 bn points / hour u Less expensive 1-head system available 50 Bildquellen: Image Riegl source: Riegl Trimble MX9 u 2 scanners u 250 Hz (per sensor) u 1000 kHz (per sensor) u “unlimited” echoes (full WF) u 3 mm precision u 7.2 bn points / hour u Less expensive 1-head system available u (Scan heads from Riegl) u (Camera: FLIR Ladybug 5, 6 x 5 MP = 30 MP) 51 Image source: www.geospatial.trimble.com IKG Mobile Mapping System Riegl VMX-250 52 IKG mobile mapping van 53 IKG mobile mapping van 54 IKG mobile mapping van 55 Badenstedt: 150 strips, ~1 bn. points 56 Badenstedt: 150 strips, ~1 bn. points 57 IKG scanning during the past years… u Total driven distance > 5,200 km u Number of scan strips > 18,600 u Number of scanned points > 225,000,000,000 (225 bn) u Tiling @ level 21 (about 11m x 11m): § > 550,000 tiles § > 76 km2 58 …most of the scans in Hannover city area 59 IKG Mobile Mapping Example (Schaufelder/ Kniestr.) 60 IKG Mobile Mapping Example (Luther Church) 61 IKG Mobile Mapping Example 62 IKG Mobile Mapping Example 63 Topcon IP-S2 (old) u Sick Scanner § 30 m (max. 80 m) § 75 Hz (line frequency) § 180°@1° or 90°@0,5° § 45 mm precision (only scanner) u Camera § 360°, 15 images/s u Typical example for early system, built from “robotics grade” components 64 Quelle: www.topconpositioning.com Topcon IP-S3 u Velodyne HDL-32 Scanner § 100 m max., 70 m typical § 5-20 Hz (line frequency) § 20 mm precision (@ 25 m) § 700,000 pulses/s § 32 lasers in parallel u Camera § 6 CCD cameras § 30 megapixel (8000 x 3000) u GNSS, IMU, wheel encoder 65 Source:https://www.topconpositioning.com/mass-data-and-volume-collection/mobile-mapping/ip-s3 Laserscanning in robotics 2005 DARPA Grand Challenge / 2007: Urban Challenge 67 Example scanners used in robotics Sick LMS Velodyne HDL-64 Hokuyo URG (here: LMS 500) (64 beams) (very small) VLP-16 VLS-128 Hesai Pandar 64 HDL-32 Ouster OS-1 (Puck) (Alpha Puck) 68 Experimental autonomous system: „Hanna“, RTS, Uni Hannover 69 How the scanner sees the world… (~91x70) 70 One scan, one extracted pole (ground points removed) 71 Automotive laser scanners Laser scanners for ADAS Image sources: IBEO, Hella IBEO Lux Hella IDIS 73 Automotive Scanner? CES 2013, Las Vegas Source: MIT Technology Review, 8.1.2013 Source: Josh Miller, CNET 74 Automotive Scanner! - Audi A8, 2017 75 Source: https://www.computerbase.de/2017-07/audi-a8-hands-on IBEO / Valeo SCALA Source: https://www.systemplus.fr 76 Automotive Scanner! - Audi A8, 2017 77 Quelle: https://www.computerbase.de/2017-07/audi-a8-hands-on / Original: Audi Interview with Clément Nouvel, Lidar Technical Product Line Director at Valeo u 08/2022 u 500 developers and engineers worldwide, Bietigheim- Bissingen, Prague, Cairo, and a few others in France, South Corea, Japan, China, India and USA u Production only in Wemding (Bavaria, Germany) u 200.000 Valeo Scanners currently on the road (08/2022) u Today, an automotive LiDAR scanner costs ~ 1,000 USD § High precision assembly § Clean rooms § However, from now on, price will drop (cf. Radar sensors, which dropped by 80% in 17 years) u More than 500.000 test kilometres driven in Europe, China, Japan, Corea, USA to get data for the algorithms (software) Source: https://www.automotiveit.eu/technology/autonomes-fahren/wir-waren-bei-lidar-schlichtweg-die-ersten-698.html 78 Automotive Scanner! - Audi A8, 2017 Quelle: https://www.computerbase.de/2017-07/audi-a8-hands-on 79 Solid state sensors: Blickfeld (Startup, Munich) 80 Image source: blickfeld.com Solid state sensors: Blickfeld (Startup, Munich) 81 Image source: blickfeld.com Sensors in self-driving cars (source: google.com) Waymo “laser bear honeycomb” 82 (source: en.Wikipedia.org) (source: wired.com) Conclusions u Laser scanners are used for mapping in § Aerial systems Fixed-wing aircrafts, helicopters, gyrocopters, UAVs/ drones § Terrestrial systems § Mobile mapping systems u Apart from mapping purposes, it is also used in § Robotics § ADAS – Advanced driver assistance systems § Self-driving cars. 83

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