Truck loading, truck box with some objects, hardware for 3D ranging (MS Kinect, Asus Xtion PRO, Sick LRF)
MSc dissertation proposal 2012/2013
Volumetrics
- Measuring Free Volumes
Introduction:
Constantly growing fuel costs imply that transporting goods using trucks
must be made more efficient than ever. Companies must keep as small as possible
the empty spaces of the truck containers.
This MSc project proposal is mainly concerned with designing an automatic free
volume estimator applied to truck containers, using recent high
resolution cameras or depth sensors such as Sick [Sick-LRF] or Hokuyo Laser
Range Finders [Hokuyo-LRF].
This project proposal is primarily though for students in the Systems
Decision and Control (SDC) branch.
Objectives:
In this work the main objective is assembling a system that allows a precise
measurement of the free volume of a truck container.
Detailed description:
Transporting goods using trucks is ubiquitous. The traditional package
sending by postal offices is nowadays widely spread among numerous cargo
transporters. Commonly, cargo transporters provide the trucks and rely on local
warehouses to perform cargo loading / unloading at their own loading docks.
Cargo transporters are constantly seeking for ways of optimizing their business
by augmenting the transported volume per truck. Assessing the not filled (free) volume
of a truck container is therefore a key tool for business optimization.
A truck container, seen from the entry point of a loading dock, is in
essence a 6 or 12 meters deep box, 2.44 meters wide and high (height in some
cases can reach 2.9 meters). Estimating the free volume, simply seen from the
entry point of the box, is a central variable to monitor. Given good estimates
of free volumes, a warehouse may decide more precisely the frequency with which
truck transportation is required.
Traditionally, the free volume has been evaluated visually by expert
dock labourers. In this MSc work proposal, the main objective is designing a
precise free volume measuring system. The system incorporates a
range measuring device, such as a depth measuring camera (e.g. MS Kinect), or a pair of high resolution cameras, or a laser
(Laser Range Finder - LRF), and a computer to control the data acquisition
device and perform the free volume computation.
The main steps of the work are therefore the following:
- Data
acquisition of depth maps using Kinect
like or LRF cameras
- Implement of the free volume estimator
- Precise definition of the nearest face of the free volume
- Analysis of the precision of the free volume estimator
Note: The hardware to use is the one already available at IST/ISR,
namely MS Kinect cameras [MS-Kinect],
high resolution cameras [PointGrey], Sick LRF
[Sick-LRF] and Hokuyo LRF [Hokuyo-LRF].
References:
[ISR-galery] Some images of
unicycle type robots at ISR: see labmate, scouts, pioneers, ... in "Mini galeria
de fotografias de projectos
@ IST/ISR", http://users.isr.ist.utl.pt/~jag/infoforum/isr_galeria/
[MS-Kinect] http://en.wikipedia.org/wiki/Kinect
[ARDC10] "Workshop on RGB-D: Advanced Reasoning
with Depth Cameras", June 27, 2010 @
[3DPR11] "European Robotics Forum 2011 WORKSHOP
RGB-D Workshop on 3D Perception in Robotics", April 8, 2011,
[CDC4CV11] "First IEEE Workshop on Consumer Depth
Cameras for Computer Vision" http://www.vision.ee.ethz.ch/CDC4CV/
November 12, 2011 @
[WDIA12] "International Workshop on Depth Image
Analysis (WDIA 2012)", In Conjunction with 21th
International Conference on Pattern Recognition 2012, November 11th, 2012,
[PointGrey] Point Grey
Research, Inc , http://www.ptgrey.com/
[Sick-LRF] http://www.sick.com/group/EN/home/products/product_portfolio/optoelectronic_protective_devices/Pages/safety_laser_scanners.aspx
(model available at IST/ISR: SICK LMS 291 )
[Hokuyo-LRF] http://www.hokuyo-aut.jp/02sensor/
(model available at IST/ISR: Hokuyo URG-04LX-UG01)
Requirements (grades, required courses, etc):
-
Expected results:
At the end of the work, the students will have enriched their experience
in computer vision, particularly in the aspect of free volume measurement.
In the end of the work is expected the publication of report(s) in the
form of research paper(s).
Place for conducting the work-proposal:
ISR / IST
More MSc dissertation
proposals on Computer and Robot Vision in:
http://omni.isr.ist.utl.pt/~jag