International audience

In this paper, visual servoing based on photometric moments is advocated. A direct approach is chosen by which the extraction of geometric primitives, visual tracking and image matching steps of a conventional visual servoing pipeline can be bypassed. A vital challenge in photometric methods is the change in the image resulting from the appearance and disappearance of portions of the scene from the camera field of view during the servo. To tackle this issue, a general model for the photometric moments enhanced with spatial weighting is proposed. The interaction matrix for these spatially weighted photometric moments is derived in an analytical form. The correctness of the modeling, effectiveness of the proposed strategy in handling the exogenous regions, and improved convergence domain are demonstrated with a combination of simulation and the experimental results.

Visual servoing based on photometric data is of great interest since it does not necessitate any image processing or visual tracking steps. A vital issue in such methods is the change in the image resulting from the appearance and disappearance of portions of the scene from the camera field-of-view during the visual servo. In this paper, we propose a spatial weighting scheme to counter this problem. A general model for photometric moments that allows for inclusion of spatial weights is presented. A custom weighting function is then chosen and specific properties of its derivative are exploited in order to develop the interaction matrix in analytical form. The resultant effects on the invariance properties are discussed. Experiments have been performed to validate the visual servoing with the proposed weighting scheme on a 4 dof robot arm.

In this paper, we introduce the concept of tunable visual features for moments based visual servoing schemes. The main contribution of this work is the introduction of tunable shift points along with some effective methods to tune them. We propose two different metrics: the first metric ensures optimal response of the control to errors in the image space and the second metric ensures orthogonality between the interaction matrix components (vectors) related to the control of x and y rotational motions. With the proposed method, it is possible to design moment invariants-based visual features whose interaction matrix is always non-singular for any desired pose (parallel or non-parallel). Thus, this work makes a significant contribution to the difficult problem of controlling the rotational motions around the x and y axes, when all the 6dof are involved. Two case studies are presented to demonstrate the validity of the proposed ideas. Results from each case are then used to design a moment invariants-based visual feature. This visual feature is used for visual servoing with a symmetrical object using binary moments and a free-form planar target using photometric moments.

In this paper, we propose a new type of visual features for visual servoing: photometric moments. These global features do not require any segmentation, matching or tracking steps. The analytical form of the interaction matrix is developed in closed form for these features. Results from experiments carried out with photometric moments have been presented. The results validate our modelling and the control scheme. They perform well for large camera displacements and are endowed with a large convergence domain. From the properties exhibited, photometric moments hold promise as better candidates for IBVS over currently existing geometric and pure luminance features.