Name
Abstract | ||
|---|---|---|
This paper addresses the problem of positioning a robot camera with respect to a fixed object in space by means of visual information. The ultimate goal of positioning is to achieve and/or to maintain a given spatial configuration (position and orientation) with respect to the objects in the environment so as to execute at best the task at hand. Positioning involves the control of 6 d.o.f. in space, which are conveniently referred to as the parameters of the transformation between a camera-centered frame and an object-centered frame. In this paper, we will address the positioning problem referring to these d.o.f.'s, regardless of the specific robot configuration used to move the camera (e.g. eye-in-hand setup, navigation platform with a robot head mounted on it, etc.). The domain of application ranges from navigation tasks, (e.g. localization, docking, steering by means of natural landmarks), grasping and manipulation tasks, and autonomous/intelligent tasks based on active visual behaviors such as reading a book or reaching and commanding a control panel. The solution proposed in this work is to exploit the changes in shape of contours in order to plan and control the positioning process. In order to simplify and speed up the calculations, an affine camera model is used to describe the changes of shape of the contours in the image plane and an affine visual servoing (AVS) approach is derived. The choice of using two-dimensional (2D) features for control greatly enhances the robustness of the positioning process, in that robot kinematics and camera modeling errors are reduced. Among the possible 2D features, visual contours enable us to achieve robust visual estimates while keeping the dimensionality of the control equations low; the same would not be possible using different features such as points or lines. Finally, a feedforward control strategy complements the feedback loop, thereby enhancing the speed and the overall performance of the algorithm. Although a stability analysis of the control scheme has not been performed yet, good simulation results with stable behavior, provided that proper tuning of control parameters and gains has been done, suggest that the approach might be successfully applied in real world cases. |
Year | DOI | Venue |
|---|---|---|
1994 | 10.1163/156855395X00517 | ADVANCED ROBOTICS |
Keywords | Field | DocType |
visual servoing,stability analysis,feedforward control,model error,feedback loop | Affine transformation,Computer vision,Spatial configuration,Control engineering,Visual servoing,Artificial intelligence,Mobile robot navigation,Control system,Engineering,Landmark,Robot,Robotics | Journal |
Volume | Issue | ISSN |
9 | 4 | 0169-1864 |
Citations | PageRank | References |
2 | 0.56 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| carlo colombo | 1 | 4 | 2.95 |
| Benedetto Allotta | 2 | 244 | 53.74 |
| Paolo Dario | 3 | 2017 | 339.00 |