Quantized Multi-Height Ocuppancy Grid Map Applied to

Name: Renan Sarcinelli
Type: MSc dissertation
Publication date: 25/02/2021

Name Rolesort descending
Thiago Oliveira dos Santos Advisor *

Examining board:

Name Rolesort descending
Thiago Oliveira dos Santos Advisor *
Filipe Wall Mutz External Examiner *
Claudine Santos Badue Internal Examiner *

Summary: The automation of cars has been widely researched and developed in the past years. Some
of the technologies embedded in self-driving cars are specific for their environments, such
as traffic sign recognition and lane marking detection. However, many of the technologies
developed for self-driving cars are extensible to general robotic applications, directly
or with some adjustments. Aiming for that opportunity, this work proposes a novel
application of traditional two-dimension occupancy grid maps, widely used in self-driving
cars, to the aircraft context of the taxiing operation. The main contributions are a new
collision representation model and a mapping generation system. This approach handles
the complex geometry of the airplane, WHERE the wings and the body have different collision
heights, the new system also introduces a more flexible collision representation model,
that reduces the movement restrictions, compared to the actual system present at IARA.
The proposed method also takes advantage of the two-dimensional localization, since
the airplane moves basically in a 2D plane during this maneuver, which is simpler when
compared to conventional three-dimensional localization and mapping systems. This work
is part of an university-industry collaboration effort to unveil the technological challenges
involved in automating such manoeuvres on an aircraft. The performance of the proposed
method was accessed in partnership with Embraer S.A., as part of an integrated proof-ofconcept
solution embedded on a Praetor 600 jet, which was able to successfully perform
an autonomous taxiing over a four miles closed circuit at a private aerodrome.
Keywords: Mapping. Grid Maps. Multi-Height. IARA.

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