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This paper deals with motion planning for a humanoid robot under task constraints. It presents a novel random method, inspired by the RRT-connect algorithm, that uses a local task solver to generate statically stable collision-free configurations. It is able to plan motions for a large variety of tasks. In an experimental section, we compare in details this random strategy with a local collision avoidance method found in the literature.