| dc.description.abstract | Unmanned Vehicles, known as UVs, have been developed to accomplish
difficult, tedious, and unpleasant missions for human beings. Their usage
started in military applications; subsequently, specific industries adopt them
to increase the productive capacity of their factories already automated with
industrial robots relying on the mobility and autonomy offered by these vehi cles. However, unmanned vehicles could operate in many other sectors - like
in agriculture, construction, logistic, customer service -, facilitating and im proving the quality of life in general. It is necessary to increase its develop ment and implementation substantially to achieve this.
As we will show in this document, progress in the area of mobile robotics,
especially in the field of unmanned vehicles, has been essential and prolifer ates. However, it is not robust yet to be reliable and accepted beyond the con trolled environments in which they operate nowadays. The enlarged area to
cover, due to mobile capabilities, plus the risky missions they need to accom plish, increases the complexity of autonomous steering and control of such a
vehicle. For this reason, the modeling considerations to achieve the task of
autonomous driving is considered complex and reserved to humans (Litman
T., 2018), due to the high frequency of interactions with other mobile objects,
which requires sensing and acting capabilities in real-time bases, with an es sential degree of intelligence and skills.
An essential step in their development is the robotics environments for de veloping and testing unmanned vehicles, these computational environments
incorporate and centralizes all technologies, in their broadest sense, related to
robotics. In both professional and academic literature, these environments are
called with different names, such as robotic middleware, robotic platform, and
robotic framework. Their degree of development and their capacities are not
homogeneous, being those specialized and commercial branded who have
reached essential levels of maturity and acceptance. As it is the case of X Plane, a platform for the simulation of autonomous flights of many well known aircraft, the Federal Aviation Administration (FAA) can even certify
the implementation if they also count on certified hardware.
Some conventional robot models are offered in these robotic environments,
which are highly used for research in robotics. It is an essential contribution
to the robotics community to get the research efforts to concentrate on the
central issues of their work. However, it does not help much if there is a need
to test a new robot model from scratch, where the initial main effort is in the
modeling and evaluation of behavior in order to redesign the model itself.
These environments also offer standard robotic functionalities that come to
help in both cases. ... [edited by Author] | it_IT |
