Optimization of Tasks Warping and Scheduling for Smooth Sequencing of Robotic Actions

Abstract : This paper presents a method for sequencing a set of robotic tasks in an optimal way. Tasks description and execution are based on the task-function approach, which enables to build complex whole-body behaviors from local control laws. A naive solution to this problem would be to schedule the execution of the tasks sequentially, avoiding concurrency. This solution does not exploit full robot capabilities such as redundancy and have poor performance in terms of execution time or energy. However, reasoning on concurrent tasks is difficult while accounting for all the physical constraints of the robot. Our contribution is to determine the time-optimal realization of the mission taking into account robotic constraints that may be as complex as collision avoidance. Our approach achieves more than a simple scheduling; its originality lies in maintaining the task approach in the formulated optimization of the task sequencing problem. This theory is exemplified through a complete experiment on the real HRP-2 robot.
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François Keith, Nicolas Mansard, Sylvain Miossec, Abderrahmane Kheddar. Optimization of Tasks Warping and Scheduling for Smooth Sequencing of Robotic Actions. IROS: Intelligent Robots and Systems, Oct 2009, St. Louis, MO, United States. pp.1609-1614, ⟨10.1109/IROS.2009.5354282⟩. ⟨lirmm-00733383⟩

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