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In this paper dynamical systems theory is used as a theoretical language and tool to design a distributed control architecture for a team
of two robots that must transport a large object and simultaneously avoid collisions with obstacles (either static or dynamic). This work
extends the previous work with two robots (see [1] and [5]). However here we demonstrate that it’s possible to simplify the architecture
presented in [1] and [5] and reach an equally stable global behavior. The robots have no prior knowledge of the environment. The dynamics
of behavior is defined over a state space of behavior variables, heading direction and path velocity. Task constrains are modeled as attractors
(i.e. asymptotic stable states) of a behavioral dynamics. For each robot, these attractors are combined into a vector field that governs
the behavior. By design the parameters are tuned so that the behavioral variables are always very close to the corresponding attractors.
Thus the behavior of each robot is controlled by a time series of asymptotic stable states. Computer simulations support the validity of
the dynamical model architecture.