Intelligent learning and control of autonomous robotic agents operating in
sharingAbstract
The control of autonomous intelligent robotic agent operating in unstructured
changing environments includes many objective difficulties. One major difficulty concerns
the characteristics of the environment that the agent should operate in. In unstructured
and changing environments the inconsistency of the terrain, the irregularity
of the product and the open nature of the working environment result in complex
problems of identification, sensing and control. Problems can range from the effects of
varying environmental conditions on the robot sensors and traction performance
through to the need to deal with the presence of unexpected situations. Another major
challenge is the large amounts of uncertainty that characterises real-world environments.
On the one hand, it is not possible to have exact and complete prior knowledge
of these environments. On the other hand, knowledge acquired through sensing is affected
by uncertainty and imprecision. The quality of sensor information is influenced
by sensor noise, the limited field of view, the conditions of observation, and the inherent
difficulty of the perceptual interpretation process. Because environments and users of
systems continuously change, robotic agents have to be adaptive. Intelligence helps
because it gives systems the capacity to adapt more rapidly to environmental changes or
to handle much more complex functions. In his paper we introduce this special issue and
introduce the difficulty robots are facing in unstructured environments and how learning Thanks for sharing this good information.
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