Eric S. Yager

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This chapter reports progress in extending the Soar architecture to tasks that involve interaction with external environments. The tasks are performed using a Puma arm and a camera in a system called Robo-Soar. The tasks require the integration of a variety of capabilities including problem solving with incomplete knowledge, reactivity, planning, guidance(More)
Robo-Soar is a high-level robot arm control system implemented in Soar. Robo-Soar learns to perform simple block manipulation tasks using advice from a human. Following learning, the system is able to perform similar tasks without external guidance. It can also learn to correct its knowledge, using its own problem solving in addition to outside guidance.(More)
Robo-Soar performs simple manipulations of blocks on a table surface using a robot arm and a camera-based vision system, and consists of several modules and communicating processes written in a mixture of Soar, Lisp, and C. The task knowledge of Robo-Soar has also been rewritten in TAQL and, more recently, using an annotated models representation. This(More)
Many satellite anomalies manifest themselves slowly over time and go undetected until they reach critical and possibly unrecoverable status. Because modern satellite systems are relatively reliable, the ground controller must perform the almost impossible task of attending carefully over long periods of time to telemetry readouts which almost always(More)
The control and navigation of unmanned ground vehicles (UGVs) by humans requires a thorough understanding of the limitations in human perception and performance. Images of the external world recorded by cameras mounted on the UGV are presented as a video display to the operator, who then remotely manipulates the vehicle using a standard control. Operator(More)
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