INFORMATION-EFFICIENT ROBOTIC CONTROL

The work demonstrates a new approach to design of a level of intellige nt control of robotic systems. The analytical model results in operati onal decisions. The structure of these decisions make them readily ava ilable to be implemented as an expert system. The approach is applied to a case study of mobile supervisory robots. The model presented here was motivated by manufacturing robotic systems and a type of autonomo us robots that collect information at different sites for safety and o ther control purposes. The robot actions are directly affected by the obtained data. At each site the amount of available information (and t hus the correctness of the robot decision) can be increased if the rob ot keeps collecting data at that site for a longer period of time. Thi s means a delay in reacting and in reaching next site and accordingly, a decrease in the general amount of robot's information on the whole system. The method of finding an economic amount of information collec ted by a robot at each site is based on the theory of controlled discr ete event stochastic systems developed in our earlier works. This theo ry combines the basic concepts of discrete event control extended to s tochastic systems with some aspects of information economics.