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Books > Professional & Technical > Energy technology & engineering > Electrical engineering
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Selected papers from the 2nd International Symposium on UAVs, Reno, U.S.A. June 8-10, 2009 (Hardcover, 2010 ed.)
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Selected papers from the 2nd International Symposium on UAVs, Reno, U.S.A. June 8-10, 2009 (Hardcover, 2010 ed.)
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In the last decade, signi?cant changes have occurred in the ?eld of
vehicle motion planning, and for UAVs in particular. UAV motion
planning is especially dif?cult due to several complexities not
considered by earlier planning strategies: the - creased importance
of differential constraints, atmospheric turbulence which makes it
impossible to follow a pre-computed plan precisely, uncertainty in
the vehicle state, and limited knowledge about the environment due
to limited sensor capabilities. These differences have motivated
the increased use of feedback and other control engineering
techniques for motion planning. The lack of exact algorithms for
these problems and dif?culty inherent in characterizing
approximation algorithms makes it impractical to determine
algorithm time complexity, completeness, and even soundness. This
gap has not yet been addressed by statistical characterization of
experimental performance of algorithms and benchmarking. Because of
this overall lack of knowledge, it is dif?cult to design a guidance
system, let alone choose the algorithm. Throughout this paper we
keep in mind some of the general characteristics and requirements
pertaining to UAVs. A UAV is typically modeled as having velocity
and acceleration constraints (and potentially the higher-order
differential constraints associated with the equations of motion),
and the objective is to guide the vehicle towards a goal through an
obstacle ?eld. A UAV guidance problem is typically characterized by
a three-dimensional problem space, limited information about the
environment, on-board sensors with limited range, speed and
acceleration constraints, and uncertainty in vehicle state and
sensor data.
General
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