Vision-based self-calibration and control of parallel kinematic mechanisms without proprioceptive sensing

International audienceThis work is a synthesis of our experience over parallel kinematic machine control, which aims at changing the standard conceptual approach to this problem. Indeed, since the task space, the state space and the measurement space can coincide in this class of mechanism, we came to redefine the complete modeling, identification and control methodology. Thus, it is shown in this paper that, generically and with the help of sensor-based control, this methodology does not require any joint measurement, thus opening a path to simplified mechanical design and reducing the number of kinematic parameters to identify. This novel approach was validated on the reference parallel kinematic mechanism (the Gough-Stewart platform) with vision as the exteroceptive sensor

Dynamic Control of the Quattro Robot by the Leg Edges

International audienceThis paper discusses variable selection for the efficient dynamic control of the Quattro parallel robot through an inverse dynamic model expressed by means of leg orientations. A selection is made within a group of variables where each can imply the state of the robot. Besides, in this work, steering a parallel robot dynamically using its self-projection onto the image plane (where the edges of the lower-legs are exploited in control) is proposed and validated for the first time. In the light of the realistic control simulation, the formative points of better control of the Quattro robot are figured out

Linear Dynamic Modeling of Parallel Kinematic Manipulators from Observable Kinematic Elements.

International audienceThis paper presents a linear method for kinematic and dynamic modeling of parallel kinematic manipulators. This method is simple, compact and clear. One can write all the equations from the beginning till the end with pen and paper. It is thus well suited to mechanical understanding and computer implementation. We can apply it to many parallel robots. This method relies on a body-oriented representation of observable rectilinear kinematic structures (kinematic elements) which form the robot legs

Image-based Visual Servoing of a Gough-Stewart Parallel Manipulator using Leg Observations

International audienceIn this paper, a tight coupling between computer vision and paral- lel robotics is exhibited through the projective line geometry. Indeed, contrary to the usual methodology where the robot is modeled indepen- dently from the control law which will be implemented, we take into ac- count, since the early modeling stage, that vision will be used for con- trol. Hence, kinematic modeling and projective geometry are fused into a control-devoted projective kinematic model. Thus, a novel vision-based kinematic modeling of a Gough-Stewart manipulator is proposed through the image projection of its cylindrical legs. Using this model, a visual ser- voing scheme is presented, where the image projection of the non-rigidly linked legs are servoed, rather than the end-effector pose

On the adequation of dynamic modelling and control of parallel kinematic manipulators.

International audienceThis paper addresses the problem of controlling the dynamics of parallel kinematic manipulators from a global point of view, where modeling, sensing and control are considered simultaneously. The methodology is presented through the examples of the Gough-Stewart manipulator and the Quattro robot

Vector-based dynamic modeling and control of the quattro parallel robot by means of leg orientations.

International audienceOne of the key steps in high-speed control of a parallel robot is to define an efficient dynamic model. It is usually not easy to have such a model for parallel robots, since many of them have complex structures. Here, we propose a vector-based approach, which employs the robot leg orientations, to obtain a simplified inverse dynamic model. At the least, this vector-based methodology is pioneering, when combined with the observation of orientations by a calibrated camera, in the sense of solving the entire control-oriented (hard) modeling problem, both kinematics and dynamics, in an almost algebraic manner through the knowledge of only a nominal set of image features: the edges of the robot legs and their time derivatives. Proposed method is verified on a simulator of the Quattro robot with a computed torque control where the leg orientations are steered

A vision-based generic dynamic model of PKMs and its experimental validation on the Quattro parallel robot.

International audienceIn this paper, we present a dynamic modeling method for parallel kinematic manipulators. This method is built upon the postures (i.e., 3D orientation vectors, lengths and self rotations) of the kinematic elements which form the kinematic chains of the robot. Regarding the structure of the above method, computer vision emerges as a good option to obtain the postures of these kinematic elements. This method is then validated experimentally on the commercial Adept Quattro parallel robot

Efficient high-speed vision-based computed torque control of the orthoglide parallel robot.

International audienceVision has often been considered as not suitable for dynamic control of robots. The experimental results presented in this paper show that it is possible to perform better with a vision based dynamic control than with a modelbased control. These results were obtained using a Cartesian computed torque control fed back, without any joint sensing, by a novel Cartesian pose and velocity estimator. The latter is designed as a virtual visual servoing scheme based on sequential acquisition of sub-images and a constant acceleration motion assumption

Constraining cosmology with shear peak statistics: tomographic analysis

International audienceThe abundance of peaks in weak gravitational lensing maps is a potentially powerful cosmological tool, complementary to measurements of the shear power spectrum. We study peaks detected directly in shear maps, rather than convergence maps, an approach that has the advantage of working directly with the observable quantity, the galaxy ellipticity catalog. Using large numbers of numerical simulations to accurately predict the abundance of peaks and their covariance, we quantify the cosmological constraints attainable by a large-area survey similar to that expected from the Euclid mission, focusing on the density parameter, Ωm, and on the power spectrum normalization, σ8, for illustration. We present a tomographic peak counting method that improves the conditional (marginal) constraints by a factor of 1.2 (2) over those from a two-dimensional (i.e., non-tomographic) peak-count analysis. We find that peak statistics provide constraints an order of magnitude less accurate than those from the cluster sample in the ideal situation of a perfectly known observable-mass relation; however, when the scaling relation is not known a priori, the shear-peak constraints are twice as strong and orthogonal to the cluster constraints, highlighting the value of using both clusters and shear-peak statistics

Towards vision-based control of cable-driven parallel robots

International audienceThis paper deals with the vision-based control of cable-driven parallel robots. First, a 3D pose visual servoing is proposed, where the end-effector pose is indirectly measured and used for regulation. This method is illustrated and validated on a cable-driven parallel robot prototype. Second, to take into account the dynamics of the platform and using a Cartesian pose and velocity estimator, a vision-based computed torque control is developed and validated in simulation