Model-based recognition and motion tracking depends upon the ability to solve for projection and model parameters that will best fit a 3-D model to matching 2-D image features. This paper extends current methods of parameter solving to handle objects with arbitrary curved surfaces and with any number of internal parameters representing articulations, variable dimensions, or surface deformations. Numerical

In this paper we discuss a method for generating a trajectory describing robot path using a sequence of noisy positions of features belonging to a moving object obtained from a robot's sensor system. In order to accurately estimate this trajectory, we show how uncertainties in the positions of object feature points can be converted into uncertainties in parameters describing the object pose (3-D position and orientation). Noisy estimations of object poses, together with their uncertainties, are then used as an input to an algorithm that approximates the desired trajectory. The algorithm is based on natural vector splines and belongs to a family of non-parametric regression techniques which enable the estimation of the trajectory without requiring its functional form to be known. Since dilemma between specifying the trajectory either in Cartesian or in joint coordinates always exists, we present both alternatives. Some simulation results are given which illustrate the accuracy of the ap...

David Lowe's influential and classic algorithm for tracking objects with known geometry is formulated with certain simplifying assumptions. A version implemented by Ishii et al. makes different simplifying assumptions. We formulate a full projective solution and apply the same algorithm (Newton's method). We report results of extensive testing of these three algorithms. We compute two image--space and six pose--space error metrics to quantify the effects of object pose, errors in initial solutions, and image noise levels. We consider several scenaria, from relatively unconstrained conditions to those that mirror real--world and real-- time constraints. The conclusion is that the full projective formulation makes the algorithm orders of magnitude more accurate and gives it super--exponential convergence properties with arguably better computation--time properties. This material is based on work supported by the Luso--American Foundation, Calouste Gulbenkian Foundation, JNICT, CAPES pro...

In this paper we review and compare several techniques for model--based pose recovery (extrinsic camera calibration) from monocular images. We classify the solutions reported in the literature as analytical perspective, affine and numerical perspective. We also present reformulations for two of the most important numerical perspective solutions: Lowe's algorithm and Phong--Horaud's algorithm. Our improvement to Lowe's algorithm consists of eliminating some simplifying assumptions on its projective equations. A careful experimental evaluation reveals that the resulting fully projective algorithm has superexponential convergence properties for a wide range of initial solutions and, under realistic usage conditions, it is up to an order of magnitude more accurate than the original formulation, with arguably better computation--time properties. Our extension to Phong--Horaud's algorithm is, to the best of our knowledge, the first method for independent orientation recovery that actually ex...

: This paper presents a new method for programming of robot trajectories. We employ the "Teaching by Showing" programming paradigm which enables the user to efficiently program robot tasks by means of vision. The user specifies the desired trajectory by moving the object to be manipulated with his own hand. The motion is measured by a stereo vision system. We take advantage of a CAD model of the object in order to facilitate the process of measurement. Smoothing vector splines are utilized to reconstruct the trajectory either in Cartesian or in joint coordinates. Uncertainties resulting from the noise of the sensors are considered explicitly in the process of reconstruction. Important points that must be reached by the robot's end-effector exactly can be specified and limitations on robot's velocities and accelerations can be set. The conversion of the reconstructed trajectory into the robot language commands is discussed. Some experimental and simulation results are presented to subs...

In this paper, we discuss how to process visual information in convoying applications, using only low--cost, off--the--shelf hardware. We introduce a numerical algorithm for real--time perspective pose estimation that uses strong task--specific constraints to achieve efficiency and stability. Through extensive experiments performed with synthetic data, we show that this approach yields more accurate recovery than a general--purpose structure--and--motion recovery framework known as the Variable State Dimension Filter, even when some of its fundamental task--specific assumptions are only partially valid. In addition, we discuss efficient ways to perform low--level vision with off--the--shelf hardware, and we present a two-- level control strategy that uses high--frequency odometry data to stabilize visual control. Real--world convoying experiments show that our tracking--and--control system performs quite well in the sense that it manages to keep targets in view, tolerates changes in li...

We present a vision-based approach to robot path planning. The programmer demonstrates a desired motion by moving an object to be manipulated with his own hand. His performance is measured with a stereo vision system. The demonstrated motion is reconstructed with the help of a non-parametric regression technique which is resistant to a considerable amount of measurement noise. The generated path is given as a linear combination of natural vector splines. The proposed methodology requires neither a geometrical model of a robot workcell, which is used by classical motion planners, nor a robot manipulator, which is needed for teaching by guiding, for the specification of the robot path. I Introduction The most widespread approach to robot path specification in the industry is teaching by guiding which involves guiding the robot through a sequence of poses which are recorded by the robot's internal sensors. This simple method, however, suffers from a number of difficulties. It forces the ...