An Intelligent Task-Planning System for Autonomous Interior-Robots

Igal M Shohet, Yehiel Rosenfeld, Abraham Warszawski

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Autonomous task-planning is a major phase within the systemic approach towards robotized performance of interior-finishing building tasks. This paper presents mathematical formulations and offers near optional solutions for three hierarchical levels of the task planning procedure. The macro-level deals with the robot's travelling among multiple rooms on a building floor. This is determined by the application of the well known "Travelling Salesman's Problem (TSP)" algorithm, in which each node on the network represents a room, and each arc represents a door between two rooms. The next main level deals with the near-optimal positioning and routing of the robot among workstations within a room. A original algorithm was developed to minimize the total cost through dynamic programming by a recursive solution. The last, micro-level of pre-planning the exact path of the tool from each workstation is briefly presented.
Original languageEnglish GB
Title of host publicationProceedings of the 11th International Symposium on Automation and Robotics in Construction
PublisherElsevier
Pages305-312
Number of pages8
StatePublished - 1994

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