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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