Autonomous goal finding quadrapod / Joshua L. Abaloyan.
By: Abaloyan, Joshua L [author]
Description: 64 leaves : 29 cmContent type: text Media type: unmediated Carrier type: volumeSubject(s): Artificial intelligence | RoboticsDDC classification: 001.535 Dissertation note: Thesis (Master in Computer Science) -- Cebu Institute of Technology - University, October 2006. Summary: This project focuses on the development of a four legged autonomous robot with fuzzy logic controller for walking speed control. The robot searches for an object in an environment and pushes the latter to a specified goal position. Searching process is done using dead reckoning technique. It uses fuzzy logic as estimator for the nearness of the object from the robot position in such way the robot will gradually slow down its speed as it is approaching the latter. While the robot is pushing the object, it maintains a slow pace in such a way the object will not be pushed away. Robot?s environment uses colored regions to help the robot know its current location and the goal position. The robot is basically a model-based reflex agent.| Item type | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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GRADUATE LIBRARY | GRADUATE LIBRARY | 001.535 T Ab16 2006 (Browse shelf) | Not for loan | CL-T1499 |
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Thesis (Master in Computer Science) -- Cebu Institute of Technology - University, October 2006.
This project focuses on the development of a four legged autonomous robot with fuzzy logic controller for walking speed control. The robot searches for an object in an environment and pushes the latter to a specified goal position. Searching process is done using dead reckoning technique. It uses fuzzy logic as estimator for the nearness of the object from the robot position in such way the robot will gradually slow down its speed as it is approaching the latter. While the robot is pushing the object, it maintains a slow pace in such a way the object will not be pushed away. Robot?s environment uses colored regions to help the robot know its current location and the goal position. The robot is basically a model-based reflex agent.
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