Mobile systems exploring Planetary surfaces in future will require more autonomy than today. The EU FP7-SPACE
Project ProViScout (2010-2012) establishes the building blocks of such autonomous exploration systems in terms of
robotics vision by a decision-based combination of navigation and scientific target selection, and integrates them into a
framework ready for and exposed to field demonstration.
The PRoViScout on-board system consists of mission management components such as an Executive, a Mars Mission
On-Board Planner and Scheduler, a Science Assessment Module, and Navigation & Vision Processing modules. The
platform hardware consists of the rover with the sensors and pointing devices.
We report on the major building blocks and their
functions & interfaces, emphasizing on the computer vision parts such
as image acquisition (using a novel zoomed 3D-Time-of-Flight & RGB camera), mapping from 3D-TOF data,
panoramic image & stereo reconstruction, hazard and slope maps, visual odometry and the recognition of potential
scientifically interesting targets.
A traffic matrix (TM)is a succinct representations of traffic
exchanges between nodes in a communication network. Such a
representation is of major interest to ISPs since it is needed to
design the network topology, perform capacity planning, configure
network routing policies, and assist in traffic engineering. Research
on TMs has taken off only recently and significant efforts are
underway to reach solutions that enable network operators to obtain
TMs systematically, either by measurement or inference approaches. In
this paper we take a step toward defining a common framework for
describing TMs. We introduce a two-level taxonomy of TMs based
on the spatial representation of network traffic used and the
aggregation level for the sources and destinations
engaging in traffic exchanges. We show that conversion between traffic
matrix types depends on the level of aggregation. Using the defined
taxonomy, we show the relationship between traffic matrix types and
their size complexity, that is, the number of elements in them. We
enumerate important network engineering and management applications
and use the taxonomy to clearly specify which type of traffic matrix
is needed for each application. We briefly discuss scalability issues
related to the methods for obtaining traffic matrices in the context
of the defined taxonomy.