Visione per il veicolo Paolo Medici 2017/ Visual Perception
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1 Visione per il veicolo Paolo Medici 2017/ Visual Perception
2 Today Sensor Suite for Autonomous Vehicle ADAS Hardware for ADAS
3 Sensor Suite Which sensor do you know? Which sensor suite for Which algorithms are required for 1. Driving in the desert 2. Driving in simplified urban environment 3. Driving in normal urban environment
4 Sensor suite Sensor Suite for Autonomous driving: Stanley Boss BRAIVE VIAC KIT Google Tesla LIDARs for Autonomous Driving ADAS Cameras for Autonomous Driving
5 Stanley - 5 LIDAR - 1 camera - 1 RADAR - GPS/IMU
6 Boss
7 Boss
8 Boss Applanix POS-LV 220/420 GPS/IMU (APLX) Submeter accuracy with Omnistar VBS corrections Tightly coupled inertial/gps bridges GPS outages SICK LMS 291-S05/S14 LIDAR (LMS) 180/90 deg 0.9 deg FOV with 1/0.5-deg angular resolution 80-m maximum range Velodyne HDL-64 LIDAR (HDL) deg FOV with 0.1-deg angular resolution 70-m maximum range Continental ISF 172 LIDAR (ISF) deg FOV 150-m maximum range IBEO Alasca XT LIDAR (XT) deg FOV 300-m maximum range Continental ARS 300 Radar (ARS) 60/17 deg 3.2 deg FOV 60-m/200-m maximum range Point Grey Firefly (PGF) High-dynamic-range camera 45-deg FOV
9
10 The BRAiVE sensing technology Front sensing 4 cameras (2 graylevel, 2 color)
11 The BRAiVE sensing technology Lateral sensing
12 The BRAiVE sensing technology Rear sensing
13 The BRAiVE sensing technology Back sensing Stereo cameras
14 BRAiVE all-round vision coverage
15 The BRAiVE sensing technology Single plane laser scanners 2 frontal, 1 backward
16 The BRAiVE sensing technology Multiplane laser scanner
17 The BRAiVE sensing technology 16 Laser beams
18 The BRAiVE sensing technology DGPS + IMU
19 BRAiVE s processing BRAiVE s data processing is performed by 4 PCs Each PC is in charge of specific sensing areas One PC is in charge of vehicle control
20 VIAC The Sensing Suite 7 cameras 4 laserscanners GPS V2V radio + Additional devices
21 KIT Two stereo rigs ( px, 54 cm base, 90 opening) Velodyne HDL-64E laser scanner GPS+IMU localization
22 KIT 2 PointGray Flea2 gray scale cameras(fl2-14s3m-c), 1.4 Megapixels, 1/2 Sony ICX267 CCD, global shutter 2 PointGray Flea2 color cameras(fl2-14s3c-c), 1.4 Megapixels, 1/2 Sony ICX267 CCD, global shutter 4 Edmund Optics lenses, 4mm, opening angle 90, vertical opening angle of region of interest (ROI) 35 1 Velodyne HDL-64Erotating 3D laser scanner, 10 Hz, 64 beams, 0.09 degree angular resolution, 2 cm distance accuracy, collecting 1.3 million points/second, field of view: 360 horizontal, 26.8 vertical, range: 120 m 1 OXTS RT3003inertial and GPS navigation system, 6 axis, 100 Hz, L1/L2 RTK, resolution: 0.02m / 0.1
23 All heights wrt. road surface 1.60 m Wheel axis (height: 0.30m) 0.06 m 0.54 m All camera heights: 1.65 m Cam 1 (gray) 0.06 m Cam 3 (color) Cam-to-Cam Rect Velodyne laserscanner & CamRect (height: 1.73 m) Cam 0 (gray) Cam 2 (color) z 1.68 m 0.80 m -to-image x y x 0.27 m z y Velo-to-Cam IMU-to-Velo GPS/IMU x (height: 0.93 m) 0.81 m 0.05 m z y 0.32 m 0.48 m 2.71 m Figure :Sensor Setup. dimensions and mounting positions of the sensors (red) with respect to the vehicle body. Heights above ground are marked in green and measured with respect to the road surface. Transformations between sensors are shown in blue. Jan 12, 2016 CSC 2541: 01-Introduction
24 What s the problem of using so many sensors? One has to Calibrate and Registered them Different 3D locations Different capture times Different types of capture: instantaneous vs scanning
25 Google Car
26 Google Car Play Video
27 Google
28 Google
29 Velodyne LIDAR
30 Velodyne HDL64 LIDAR
31 Different Velodyne LIDARs
32 IBEO LIDARs
33 Tesla Sensor Suite
34 Tesla Sensor Suite A forward radar A forward-looking camera 12 long-range ultrasonic sensors positioned to sense 16 feet around the car in every direction at all speeds GPS A high-precision digitally-controlled electric assist breaking system Autopilot is on the Market on Model S
35 ADAS Active Park Assist Lane Departure Warning Traffic Sign Recognition Adaptive Cruise Control / ACC Stop & Go Forward Collision Warning / Emergency Breaking Blind Spot Detection Intelligent HeadLamp Control Pedestrian Detection
36 ADAS
37 ADAS
38 ADAS
39
40
41 ADAS
42 ADAS
43 Camera Sensor Resolution Pitch Size Technology Sensitivity Lens FOV Aperture Automotive Hardware problem
44 Autonomotive Hardware AEC-Q100 standard Operating temperature Grade 0: -40 C to +150 C Grade 1: -40 C to +125 C Grade 2: -40 C to +105 C Grade 3: -40 C to +85 C Grade 4: 0 C to +70 C Storage Temperature (higher!) Mechanical Shock Vibration
45 CCD Good Sensitivity Optical Blooming!
46 CCD vs CMOS
47 Rolling Shutter
48 Rolling vs Global
49 Rolling Shutter
50 Rolling Shutter
51 Rolling Shutter Each image row (pixel) has different time Pixels of dewarped image have a complex time equation Precise disparity on rectified image is impossible
52 Aperture vs Shutter f/ lens aperture: Depth of Field Light = Lens Aperture = proportional to 1/f 2 Shutter (Exposure) time: light acquired by pixel proportional to shutter
53 Light Conversion Shutter: light vs motion blur light α shutter Aperture: light vs depth of field light α 1/f 2 Pixel size (Pitch size): light vs resolution light α pitch 2 Sensitivity/Capacity
54 Dynamic Range problem DAY: >10^5 lux NIGHT: <10^-1 lux Dynamic Range: ~120db
55 Dynamic Range 8 12 bit ADC: 8 bit 256:1 48db 10bit 1024:1 60db 12bit 4096:1 72db bit 1M:1 120db Hardware vs Multiple Shot Non Linear Mapping Local Mapping (ToneMapping )
56 HDR Hardware
57 HDR MultiShot Images copyright Vislab/Ambarella Inc.
58 HDR Blending X1 =X1+noise X2 =X2+noise A = T2/T1 X1 = A * X1 X =X2 *f2+x1 *f1
59 Video Sensors Good Image Quality: High Sensitivity over a wide Spectrum and Wide Dynamical Range broad temperature range: -40degC degC Some applications also require Color Global Shutter = Expensive! Rolling Shutter = Distortion!
60 WindShield distortion Lens distortion model is radial Windshild distortion is not radial! Spline?
61 Additional Issue Thermal stability: lens parameters, calibration parameters can change during time due to temperature changes. Real Time Calibration? Autocalibration
62 Hardware for ADAS Last Challenge: Energy Efficiency AlphaGo: 1920 CPUs and 280 GPUs, $3000 electric bill per game on mobile: drains battery on data-center: latency? increases TCO
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