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- W2018117885 abstract "A near time-optimal inspection-task-sequence planning for two co operative industrial robots is outlined. The objective of the task- sequence planning is not only to find a series of near time-optimal final configurations for two arms where the inspection operations are undertaken for segment motions, but also to find a near time-optimal task sequence of inspection points. A time-efficient, continuous joint-acceleration profile is proposed for a class of general industrial robots, and simplified by suitably choosing the time intervals of the profile for each segment motion between any two points to be inspected. The optimization problem to find near time-optimal final configurations is solved using the non linear optimization method of sequential quadratic programming (SQP). The computation overhead arising with this approach is suc cessfully dealt with. The task-sequence planning is formulated as a variation of the travelling salesman problem, and simulated anneal ing is used to find a near time-optimal route. The near time-optimal task-sequence planning and time-efficient trajectory planning are effectively integrated with the related computational problems ad dressed and solved. The proposed method is applied to an environment containing two RTX SCARA-type industrial robots with six joints. Computations have been carried out for moving points in a route, as compared with the same fixed points in a route where only one arm moves. The conclusion is that it is much more efficient if two robot arms work in a cooperative mode. A speed increase by a factor of close to 3 has been achieved through effective use of joint capabilities in the cooperative system. Experiments have also been conducted on the RTX system, yielding satisfactory results that are consistent with those obtained by simulation." @default.
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- W2018117885 date "1998-08-01" @default.
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- W2018117885 title "A Practical Approach to Near Time-Optimal Inspection-Task-Sequence Planning for Two Cooperative Industrial Robot Arms" @default.
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- W2018117885 doi "https://doi.org/10.1177/027836499801700804" @default.
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