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ARTIFICIAL COGNITIVE SYSTEMS IN FLEXIBLE ASSEMBLY. Tomasz Kosicki. VS. INDUSTRIAL ROBOT. HUMAN WORKER. Please, find proper tools, and assembly this 5 components. If you have questions, take a look on the drawings, or ask me. OK!. A screw , hmm … I will need a screw driver, and ….
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ARTIFICIAL COGNITIVE SYSTEMSIN FLEXIBLE ASSEMBLY Tomasz Kosicki
VS. INDUSTRIAL ROBOT HUMAN WORKER
Please, find proper tools, and assembly this 5 components. If you have questions, take a look on the drawings, or ask me. OK! A screw, hmm … I willneed a screw driver, and … ..besides be careful with the aluminum sheet. It shouldn’t be bent!
#%&# !? Please, find proper tools, and assembly this 5 components. ? If you have questions, take a look on the drawings, or ask me. ..besides be careful with the aluminum sheet. It shouldn’t be bent! NOT FLEXIBLE NOT INTELLIGENT
HUMAN WORKER INDUSTRIAL ROBOT programming /implementations TEACHING explanations/demonstrations previous experience concept network no experience CAD/CAM models KNOWLEDGE PROBLEM SOLVING solving by analogies hypotheses and verifications computational intelligence optimizations symbolic data (objects, events etc.) classical data (numbers, categories etc.) DATA
CAD/CAM MODELS INDUSTRIAL ONTOLOGY ENVIRONMENT SYMBOLIZER SENSOR NETWORKS SYMBOLIC CONTROL SYSTEM HUMAN-MACHINE INTERFACE DE-SYMBOLIZER DE-SYMBOLIZER CLASSICAL CONTROL SYSTEMS HUMANS MACHINES
CHALLENGES: • Symbolic Data Acquisition • Symbolic Data Analysis • Symbolic Artificial Intelligence • Symbolic Control System • GOAL OF THE RESEARCH: • Propose structure of the system • Build simple working system POTENTIAL ACHIEVEMENTS: Completely new approach to design assembly and in general manufacture systems.