SENSOR FUSION - Laser and Camera
Camera
Laser Range Finder
 direct depth measurement
 illumination dependent
 wide accuracy span (till 200 m)
 accurate only for limited distances
 only 2 or 3 D contour
 info on colour and texture
 high computational time
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Programma - LASER + CAMERA
MEASUREMENT BY LASER and CAMERA
• Laser rangefinders, principles and applications
• Laser-Camera Calibration
MEASUREMENT BY LASER and CAMERA: object recognition
• Clustering and segmentation of the scene seen by the laser
• Chamfer distance (or Hausdorff)
MEASUREMENT BY LASER and CAMERA: object recognition
• reprojection of the object model of CCD
• Corner extraction
• Matching and acceptance
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Programma - LASER + CAMERA
MEASUREMENT BY LASER and CAMERA: object recognition
• Practice with real data. The scene will be a box of given size to be recognized
MEASUREMENT BY LASER and CAMERA: object recognition
• Practice with real data.
SUPERQUADRICHE
• General concepts
SUPERQUADRICHE
• Application to object recognition
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Programma - esercitazione
SENSOR FUSION of timeline signals
- Complementary Filtering. Theory and applications. Example of simulation of an
altimeter baro-inertial.
SENSOR FUSION of timeline signals
- Simulation PC in the classroom portion of the estimate by filtering between a
barometer and an inertial platform
SENSOR FUSION of timeline signals
- Use of real data:
- Measurement of the camera position by means of an object in motion on a plane by
means of KLT, after having calibrated the worktop (using a grid placed on the floor)
- Combined with the accelerometer data and complementary filtering
Telecamera + oggetto sul piano
con accelerometro solidale
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Programma - sensor fusion + esercitazione
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Programma - sensor fusion + tesina
SENSOR FUSION
- Statistical concepts accessories, Bayes' Theorem
SENSOR FUSION
- Application of Bayes' theorem to the fusion of information scalar and vector
SENSOR FUSION
- Kalman Filter
SENSOR FUSION. Tutorial SLAM + Kalman. Mapping with laser scanner or camera
SENSOR FUSION. Tutorial SLAM + Kalman. Mapping with laser scanner or camera
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Programma - sensor fusion + tesina
MOBILE ROBOT - Overview of applications. Localization issues, planning and
control, holonomic and non-linear differential constraints. Conditions of integrability,
Model Differential Drive. Recursive equations for odometry.
MOBILE ROBOT - Models kinematic unicycle, bicycle and bicycle trailers with N
MOBILE ROBOT - Problem of planning. Classification. Transformation of kinematic
models in chained form.
MOBILE ROBOT - Planning open-loop. Systems in chained form for the solution of
the motion point-to-point with sinusoidal input, wise constant, polynomial. Calculation
of Cartesian trajectories eligible
MOBILE ROBOT - Planning open-loop. Clothoids and polar spline. Examples of
calculation.
MOBILE ROBOT - Controllability of systems that are not holonomic. Example of
control system in chained form linearized around the desired trajectory
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Programma - robot mobili
Exam: homework + 1 ORAL ARGUMENTS ON 2
CHOICES (between 4 topics, which does not coincide with
that of the homework), [NOTE: 1 topic for mehanics area]
Homework chose examples:
trajectory control of manipulators by inverting the
differential kinematics (CLASS)
simulation and trajectory control for non-holonomic
vehicles
processing data for the calibration kinematics of an
autonomous vehicle AGV
SLAM using a laser scanner at 360 °
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Modalità di esame
L.Sciavicco, B. Siciliano, Robotica - Modellistica, pianificazione e
controllo 3/ed, McGraw
Mitchell Harvey, "Multi-Sensor Data Fusion: An Introduction" - Springer
2007
Ake Bjork, Numerical methods for least squares problems
M. De Cecco, Lucidi del corso di Robotica e Sensor Fusion
Luca Baglivo, M. De Cecco, Navigazione di Veicoli Autonomi Fondamenti di “sensor fusion” per la localizzazione
L. Baglivo, Navigazione di Veicoli Autonomi (Localizzazione,
Pianificazione e Controllo traiettoria)
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion
Testi Consigliati
VIDEO
M. De Cecco - Lucidi del corso di Robotica e Sensor Fusion