DIRECTIONAL CORRECTION AMOUNT MODEL FORMATION METHOD OF TUNNEL ROBOT
PURPOSE:To form a directional correction amount model of a small diametric tunnel robot by a neural network not using offset value as input. CONSTITUTION:Pitching angles thetahp(k)-thetahp(k-n) of the present and the past heads of a tunnel robot and pitching angle variation DELTAthetap(k-1)-DELTAthe...
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| creator | YAMADA TAKAYUKI AOSHIMA SHINICHI HANARI KENICHI YABUTA TETSUO |
| description | PURPOSE:To form a directional correction amount model of a small diametric tunnel robot by a neural network not using offset value as input. CONSTITUTION:Pitching angles thetahp(k)-thetahp(k-n) of the present and the past heads of a tunnel robot and pitching angle variation DELTAthetap(k-1)-DELTAthetap(k-n) are made as input of an input layer, and a neural network 11 of three layer construction making the present pitching angle variation DELTAthetap(k) as output of an output layer is used. The relation between 'pitching angles of the present and the past heads and the past pitching angle variation of a robot body in the case of the actual execution and the present pitching angle variation' is learned by learning rules of the neural network 11 as learning data. According to the constitution, when 'pitching angles of the present and the past heads and the past pitching angle variation of a robot body' are inputted, a directional correction amount model is formed by the neural network outputting 'the present pitching angle variation'. |
| format | Patent |
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CONSTITUTION:Pitching angles thetahp(k)-thetahp(k-n) of the present and the past heads of a tunnel robot and pitching angle variation DELTAthetap(k-1)-DELTAthetap(k-n) are made as input of an input layer, and a neural network 11 of three layer construction making the present pitching angle variation DELTAthetap(k) as output of an output layer is used. The relation between 'pitching angles of the present and the past heads and the past pitching angle variation of a robot body in the case of the actual execution and the present pitching angle variation' is learned by learning rules of the neural network 11 as learning data. 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CONSTITUTION:Pitching angles thetahp(k)-thetahp(k-n) of the present and the past heads of a tunnel robot and pitching angle variation DELTAthetap(k-1)-DELTAthetap(k-n) are made as input of an input layer, and a neural network 11 of three layer construction making the present pitching angle variation DELTAthetap(k) as output of an output layer is used. The relation between 'pitching angles of the present and the past heads and the past pitching angle variation of a robot body in the case of the actual execution and the present pitching angle variation' is learned by learning rules of the neural network 11 as learning data. According to the constitution, when 'pitching angles of the present and the past heads and the past pitching angle variation of a robot body' are inputted, a directional correction amount model is formed by the neural network outputting 'the present pitching angle variation'.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | CONTROL OR REGULATING SYSTEMS IN GENERAL CONTROLLING EARTH DRILLING FIXED CONSTRUCTIONS FUNCTIONAL ELEMENTS OF SUCH SYSTEMS GALLERIES LARGE UNDERGROUND CHAMBERS MINING MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS ORELEMENTS PHYSICS REGULATING SHAFTS TUNNELS |
| title | DIRECTIONAL CORRECTION AMOUNT MODEL FORMATION METHOD OF TUNNEL ROBOT |
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