Challenges in border security may be resolved through a team of autonomous mobile robots configured as a flexible
sensor array. The robots will have a prearranged formation along a section of a border, and each robot will attempt to
maintain a uniform distance with its nearest neighbors. The robots will carry sensor packages which can detect a
signature that is representative of a human (for instance, a thermal signature). When a robot detects an intruder, it will
move away such that it attempts to maintain a constant distance from the intruder and move away from the border (i.e.
into its home territory). As the robot moves away from the border, its neighbors will move away from the border to
maintain a uniform distance with the moving robot and with their fixed neighbors. The pattern of motion in the team of
robots can be identified, either algorithmically by a computer or by a human monitor of a display. Unique patterns are
indicative of animal movement, human movement, and mass human movement. To realize such a scheme, a new control
architecture must be developed. This architecture must be fault tolerant to sensor and manipulator failures, scalable in
number of agents, and adaptable to different robotic base platforms (for instance, a UGV may be appropriate at the
southern border and a UAV may be appropriate at the northern border). The Central Arkansas Robotics Consortium has
developed an architecture, called Layered Mode Selection Logic (LMSL), which addresses all of these concerns. The
overall LMSL scheme as applied to a multi-agent flexible sensor array is described in this paper.
Robots developed from the 60's to the present have been restricted to highly structured environments such as work cells
or automated guided vehicles, primarily to avoid harmful interactions with humans. Next generation robots must
function in unstructured environments. Such robots must be fault tolerant to sensor and manipulator failures, scalable in
number of agents, and adaptable to different robotic base platforms. The Central Arkansas Robotics Consortium has
developed a robot controller architecture, called Layered Mode Selection Logic (LMSL), which addresses all of these
concerns. The LMSL architecture is an implementation of a behavior based controller fused with a planner. The
architecture creates an abstraction layer for the robot sensors through a Fuzzy Sensor Fusion Network (FSFN), and it
creates an abstraction layer for the robot manipulators through a reactive layer. The LMSL architecture has been
implemented and tested on UALR's J5 robotics research platform. A FSFN combines acceleration and force signals for
collision detection. The output of the FSFN switches among low level behaviors to accomplish obstacle avoidance and
obstacle manipulation. Comparable results are achieved with all sensors functioning, with only the acceleration sensor
(force sensor faulted), and with only the force sensor (acceleration sensor faulted).
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