We propose a set of control strategies for performing two arm manipulation with the goal of simplifying the task definition. In order to develop these strategies we propose a new representation, derived from the cooperative task-space, in the dual quaternion domain. The result is a compact and "singularity free" representation for two arm systems, named cooperative dual task-space. All the proposed control strategies share the same general scheme and are derived by using an analytical approach. Moreover, the mathematical treatment is given in a coherent and systematic fashion, and thus other strategies may be derived using the same argument. Experimental results show the effectiveness and usefulness of the cooperative dual task-space framework and the proposed control strategies.

In this paper, we address the problem of pair-wise registration of large unstructured 3D/color datasets. Our purpose is to improve the classical ICP (Iterative Closest Point) algorithm by using color information, in order to deal with large datasets and with objects for which the geometric information is not significant enough. After a brief presentation of classical ICP (Iterative Closest Point) algorithm and of the research works developed to improve its performance, we propose a new strategy to improve the selection of points. Color information is used to reduce the search space during the matching step. Experimental results obtained with real range images show that the algorithm provides an accurate estimation of the rigid transformation.

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