| 1. |
- Johansson, Rolf, et al.
(författare)
-
Sensor Integration in Task-level Programming and Industrial Robotic Task Execution Control
- 2004
-
Ingår i: Industrial Robot. - : Emerald. - 0143-991X. ; 31:3, s. 284-296
-
Tidskriftsartikel (refereegranskat)abstract
- Presents an approach to improved performance and flexibility in industrial robotics by means of sensor integration and feedback control in task-level programming and task execution. Also presents feasibility studies in support of the ideas. Discusses some solutions to the problem using six degrees of freedom force control together with the ABB S4CPlus system as an illustrative example. Consider various problems in the design of an open sensor interface for industrial robotics and discusses possible solutions. Finally, presents experimental results from industrial force controlled grinding.
|
|
| 2. |
- Bengtsson, Johan, et al.
(författare)
-
A Robot Playing Scrabble Using Visual Feedback
- 2000
-
Ingår i: IFAC Proceedings Volumes. ; 33:27, s. 551-556
-
Tidskriftsartikel (refereegranskat)abstract
- Today most industrial robot systems use dedicated and rather limited sensors, and available control systems provide limited support for feedback control. Aiming towards more autonomous robot systems, we want to improve flexibility. The game Scrabble is used as a test problem capturing these aspects. Our approach is to incorporate visual servoing and a conventional powerful off-line prograrnrning (OLP) system into the real-time control system, providing task specification and visual debugging. We use the OLP tool Envision from Deneb and an ABB robot with reconfigured control system, where the control system has an Open Robot Control architecture (ORC). The vision system is connected to a host computer and the camera is attached to the robot gripper. By extending the control system, we have designed and implemented both the vision system and the application for the Scrabble game. Our system implementation shows that ORC constitutes a necessary support for incorporation of real-time visual feedback and that OLP may effectively be used with real-time feedback of sensor data.
|
|
| 3. |
- Olsson, Tomas, et al.
(författare)
-
Flexible Force-Vision Control for Surface Following using Multiple Cameras
- 2004
-
Ingår i: Proceedings. 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004. (IROS 2004).. - 0780384636 ; 1, s. 789-803
-
Konferensbidrag (refereegranskat)abstract
- A flexible method for six-degree-of-freedom combined vision/force control for interaction with a stiff uncalibrated environment is presented. An edge-based rigidbody tracker is used in an observer-based controller, and combined with a six-degree-of-freedom force- or impedance controller. The effect of error sources such as image space measurement noise and calibration errors are considered. Finally, the method is validated in simulations and a surface following experiment using an industrial robot.
|
|
| 4. |
- Olsson, Tomas, et al.
(författare)
-
Visual Position Tracking using Dual Quaternions with Hand-Eye Motion Constraints
- 2003
-
Ingår i: Proceedings. ICRA '03.. - 2152-4092 .- 1050-4729. - 0780377362 ; 3, s. 3491-3496
-
Konferensbidrag (refereegranskat)abstract
- In this paper a method for contour-based rigid body tracking with simultaneouscamera calibration is developed. The method works for a singleeye-in-hand camera with unknown hand-eye transformation,viewing a stationary object with unknown position. The method usesdual quaternions to express the relationship between the camera- andend-effector screws. It is shown how using the measured motion of therobot end-effector can improve the accuracy of theestimation, even if the relative position and orientation between sensorand actuator is completely unknown.The method is evaluated in simulations on images from a real-time 3D renderingsystem. The system is shown to be able to track the pose of rigid objects and changes in intrinsic camera parameters, using only rough initial values for the parameters. The method is finally validated in anexperiment using real images from a camera mounted on an industrial robot.
|
|
