16.06.09State of the art and research perspectives at DISCo1 Informatica e Robotica per lAutomazione...

16.06.09 State of the art and research perspectives at DISCo 1

Informatica e Robotica per l’Automazione (IRA) Lab.

Informatica e Robotica per l’Automazione (IRA) Lab.

Dipartimento Informatica, Sistemistica e Comunicazione,

Università degli Studi di Milano – Bicocca

Domenico G. Sorrenti

[email protected]

http://www.disco.unimib.it/sorrenti

lab. website: http://www.ira.disco.unimib.it

http://www.ira.disco.unimib.it/

http://www.ira.disco.unimib.it/


Research activities

In the IRAlab we pursue research in autonomous systems;

Most of our work concerns autonomous robots;

What are autonomous robots? Let’s see 3 examples.


Autonomous robots - example 1



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So, what are autonomous robots?

A machine that receives information from its working environment by means of its sensors, and basing on this information decides autonomously what action to execute, out of the ones available, in order to pursue a given task.

Perception

Action

Decision

Percezione

Azione

Decisione

Perception

Action

Decision


Autonomous robots as controllers

modeling of physics

probabilistic reasoning

programming

analog and digital electronics

complex modeling of physics

control systems

programming


Staff

Domenico G. Sorrenti, assoc. prof. Daniele Marzorati, research assoc. Axel Furlan, research assist. students


Main research topics

Vision-based SLAM (Simultaneous Localization and Mapping);

Multi-target tracking;

Benchmarking, a cultural approach, orthogonal to the topics.


Vision-based SLAM

costruzione di un modello (mappa) dell’ambiente di lavoro


Vision-based SLAM we tackled the uncertainty modeling problem, relevant in vision-

based SLAM; we are now at the frontier of the research, at the international level,

with the “inverse scaling” parameterization; expectations:

to consolidate the results publishing comparisons with other proposals on known benchmarks;

to handle large maps (CISLAM approach from Zaragoza); to handle dynamic scenes;

this is a joint work with Politecnico di Milano; cooperation: Universidad de Zaragoza, Albert Ludwig Universiteit

Freiburg;


Multi-target tracking


Multi-target tracking we tackled the problem of handling ambiguities in tracking, relevant

in vision-based navigation (indoor and outdoor); in this field we are now behind the frontier of the research, at the

international level; expectations:

to publish our current results in papers based on comparisons with other proposals, on known benchmarks;

to integrate with the research in SLAM o increase accuracy in both systems;

to apply our systems to both indoor (project Grandi Attrezzature 2008) and outdoor (robotic cars/buses) navigation.

cooperation: Politecnico di Milano


Benchmarking in SLAM


Benchmarking in SLAM we tackled the problem of procuring datasets for benchmarking of SLAM algorithm by

any research groups, in a project funded by the EEC, quite successful; this is a “support of the research” activity, though innovation had to be brought in for:

the definition of the Ground Truth collection systems for the robot pose, the definition of performance measures, the definition of some algorithms, i.e., benchmark solutions;

in this field we are the frontier of the research, at the international level; expectations:

to publish our results in papers devoted to robotic benchmarking; to apply our SLAM research results to the collected datasets; to maintain the lead in the field, e.g., by using the Grandi Attrezzature 2008 infrastructure for

benchmarking research fields where offline datasets are not viable. cooperation: Politecnico di Milano, Universidad de Zaragoza, Albert Ludwig

Universiteit Freiburg;


Why robotics is different? Taxonomy of research activity:

at the conceptual level: pure pencil and paper work; at the software implementation level: software development; at the hardware level: robotics, and other “real” research activities.

Real example: during the “Sant’Ambrogio” week in December 2008 about 10 people from UNIMIB and

POLIMI spent the something more than one week, after preparing for this activity, collecting indoor datasets for SLAM benchmarking in the Bicocca location.

about 8 top-qualified people from UNIZR and ALUFR spent at about the same amount for checking and validating the datasets.

End of January it turned out that a bug in a newer version of the IEE1394 (Firewire) driver invalidated all such datasets.

The datasets had to be re-collected; it took about one month of full pipelined work for the same number of people, which amounts to more than one year of labor.

Pure pencil and paper research do not risk such troubles, and the same applies to pure software research.


Conclusions Both SLAM and multi-target tracking are required for

autonomous driving, in any application: robotized car/buses, indoor autonomous navigation services, unmanned ground / air / underwater vehicles.

In a few years many robotic product will reach the market; shall we be ready for selling them or we will be just customers?

16.06.09State of the art and research perspectives at DISCo1 Informatica e Robotica per lAutomazione...

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