Abstract
A general agreed approach on mission and motion planning consists in splitting it into three steps: decomposing the mission into a sequence of tasks (task planning), determining the order of realization and the timing of the tasks (task scheduling) and finally executing the task sequence. This approach maintains the task component in the entire reasoning, using it as a bridge between planning, scheduling and execution.In the sense of task function, a task defines a control law on part of the robot. Hence, for highly redundant systems such as humanoid robots, it is possible to realize several tasks simultaneously using a stack-of-tasks formalism. Though, classical schedulers do not handle the case where the motion is specified not by one, but by a combination of tasks organized into a hierarchy. As a result, the scheduling phase is usually skipped. This thesis aims at reintroducing the scheduling phase, while maintaining the central role of the task.First, the stack-of-tasks formalism is recalled and the continuity of the control law is studied. Particularly, we show that discreet operations (insertion, removal and swap of priority between tasks) create discontinuities in the control. We then present and discuss smoothing methods. Second, we present a task-overlapping based method to optimize not only the scheduling but also the behavior of the tasks of a given sequence, while accounting for the physical constraint of the execution. Finally, we introduce a new perspective in the usage of the task-function approach the task function approach to personalize a task sequence and take into account user preferences.These results are experimented on the humanoid robot platform HRP-2.