François Chaumette

Robot Control Using Disparate Multiple Sensors

A simple and efficient control algorithm that combines several sensors in order to realize the positioning task of a robot end effector is presented in this paper. The multiple-sensor control was designed as a part of the task function approach. A particular choice of the task function allows the researcher to simplify the design of the control law and the stability analysis. This global controller is based on the weighted sum of individual task functions. The approach was applied to the control with vision and force sensors. In spite of its simplicity, this approach provides satisfactory experimental results. Improvements in the positioning of cumbersome objects were obtained using cameras observing different parts of a scene. Moreover, peg-in-hole insertion experiments involving large initial errors were performed using a seven-axis robot manipulator without any computation of the peg trajectory by combining vision and force sensors.

Revisiting the Determination of the Singularity Cases in the Visual Servoing of Image Points Through the Concept of Hidden Robot

The determination of the singularity cases in visual servoing is a tricky problem, which is unsolved for most of the image-based approaches. In order to avoid singularities, redundant measurements may be used. However, they lead to the presence of local minima. Moreover, they do not always ensure that singularities can be avoided. Here, we show that a concept named the “hidden robot,” which was formerly used for understanding the singularities of a vision-based controller dedicated to parallel robots, can be used for interpreting the singularities in the visual servoing of image points. These singularity cases were already found in the case in which three points are observed, but we show that the hidden robot concept considerably simplifies the analysis by using geometric interpretations of the mapping degeneracy and tools provided by the mechanical engineering community. Moreover, to the best of our knowledge, for the first time, we provide the singularity conditions when more than three points are observed. We also discuss how these tools could be extended in order to find the singularity cases of other visual servoing techniques (e.g., when lines are observed).

Determining the Singularities for the Observation of Three Image Lines

The determination of the singularity cases in the observation of image features is a complicated problem, which is still open, apart from image points. For the first time, we provide the singularity cases in the observation of three image lines. We show that a concept named the “hidden robot,” which was formerly used for understanding the singularities of a vision-based controller dedicated to parallel robots and, more recently, which proved to be efficient for finding the singularity cases in the observation of image points, can be used for interpreting the singularities in the observation of three image lines. The hidden robot concept considerably simplifies the analysis by using geometric interpretations of the mapping degeneracy and tools provided by the mechanical engineering community. We prove that in the most complicated case where three general lines in space are observed, singularities appear when the origin of the observed object frame is either on a quadric or a cubic surface whose location in space depends on the configuration of the observed lines. In simpler cases where at least two lines belong to the same plane, these two surfaces can degenerate into simpler geometrical loci (e.g., planes, cylinders, and lines).