Dedicated robot-robot cooperation.

Grigorescu, Sanda ; Vatau, Steliana ; Dobra, Andreea 等

1. INTRODUCTION

Cooperation has been the key to success of most human endeavour; the similar incorporation of cooperation in robotic systems is critical to realize the next generation of systems and applications. Interest in cooperating systems arises when the tasks may be too complex for a single system to accomplish, or when building and using several simple systems can be more flexible, fault-tolerant or cheaper than using a single large system. In recent years, cooperative robots have continued to receive a great deal of attention from both the robotics research community and the robotics industry. The cooperation of multiple manipulators can extend the fields where robots can be used effectively. Synchronization, coordination, and cooperation are intimately linked subjects, and sometimes it used as synonymous to describe the same kind of behaviour, mainly in mechanical systems. Typically robot coordination and cooperation of manipulators (Liu et al., 1997) form important illustrations of the same goal. It is desired that two or more mechanical systems, either identical or different, are asked to work in synchrony. In robot coordination the basic problem is to ascertain synchronous motion of two (or more) robotic systems. This is obviously a control problem where, at least for one of the robots, a suitable feedback controller has to be designed such that this robot (slave) follows the other robot (master). This problem is further complicated by the fact that frequently only position measurements of both master and slave robots are available. This partial access to the state of the system has been the reason for developing model-based observers which are integrated in the feedback control loop. In practice, robot manipulators are equipped with high precision position sensors, such as encoders. Meanwhile new technologies have been design for measuring velocities, e.g. brushless AC motors with digital servo-drivers. Nevertheless such technologies are not yet common in applications. Therefore, velocity measurements are often obtained by means of tachometers which are contaminated by noise. Moreover, velocity sensor equipment is frequently omitted due to the savings in cost, volume and weight that can be obtained. For these reasons, a number of model-based robot control methods have been proposed (Nicosia & Tomei, 1990). In these methods a velocity observer is integrated in the control loop, although exact knowledge of the non-linear robot dynamics is assumed, which in practice is generally not available. To overcome this drawback, robust tracking controllers only based on position measurements have been proposed (Rodriguez-Angeles & Nijmeijer 2001). However, all the mentioned before papers deal with the tracking control problem and not with the robot coordination problem. The problem of coordinating (synchronizing) physical systems can be seen as tracking between two physical systems. Although it seems to be a straightforward extension of classical tracking controllers, this problem implies challenges that are not considered in the design of tracking controllers. Most of the tracking controllers are based on full knowledge of the desired reference to be tracked, and no one predicts what would happen in the case of partial knowledge of the reference signal, or how to deal with it. Cooperative manipulation is an important capability for extending the domain of robotic applications. It allows multiple robots to work together in such way that results a significant increase in their overall effective workload and workspace. For many tasks, the use of heterogeneous robots is indicated because of the difficulties of constructing a single robot that has the needed size, strength, dexterity, etc. One such application domain is assembly of large-scale structures, such as terrestrial buildings, planetary habitats, or space solar power structures. Such domains need both heavy lifting capabilities, as well as precise, dexterous manipulation to connect parts together. Another application is in industrial field, where is necessary to handling different kind of object (see fig. 1).

[FIGURE 1 OMITTED]

2. SYSTEM AND COOPERATION TASK DESCRIPTION

The robot cooperation was studied on the two "Eshed Robotec" robots; these are components of a small scale Flexible Manufacturing System (FMS). The structure of the system consists of three stations: the ASRS, the Milling and the Assembly Workstations. The systems layout is presented in figure 2.

Notations used in figure 2:1-The Storage Carousel; 2-ER VII Robot; 3-ER VII Controller; 4-Conveyor Pallet; 5-Pallet Stop Stations; 6-Conveyor; 7-Conveyor PLC; 8-Milling Machine; 9-Milling Machine CNC; 10-ER V+ Robot; 11-ER V+ Controller; 12-Station Buffers; 13-PC for Station 2; 14-Central PC; 15- Central Controller; 16-PC for Station 3; 17-Scora ER 14 Robot; 18-Assembly Table; 19-XY Motions Table.

[FIGURE 2 OMITTED]

The Central and Station PC's carry out different functions, among them is Human-Machine Interface for on-line robotic system visualization, programming and set-up. The control architecture of FMS is hierarchical, the Central Controller achieves the sequences of whole production (sends commands and receives rapports to/from Robot Controller), via RS 232 ports.

The two robots have RRRRR joints, but different mechanical structure and different workspace dimensions.

The collaboration possibilities between the two robots ER VII and ER V+ include motion synchronisation (the same motion in the same time), cooperation (different motions in the same time for a common goal) and coordination master-slave (master robot's motion followed up by slave robot's motion). Due to the relative robot installation, the cooperation refers to the large dimensions pieces manipulation.

The paper's proposed tasks are synchronous motions of ER VII and ER V+ robots, on linear and full circle trajectories. The ER VII is considered the master robot, with programmed poses, which are transformed in slave robot ERV+ position coordinates. The motion speed on both robots is constant and the programmed values are determined experimentally.

3. APPLICATION ALGORITHMS AND RESULTS

The application problems were:

* Measure the base reference system attached to a piece in the workspace of both robots: P1 for ER VII ([sup.P1][T.sub.R1]) and P2 for ER V+ ([sup.R2][T.sub.P2]).

* Finding out the transformation matrix [sup.P2][T.sub.P1].

* Finding out the transformation matrix:

[sup.R2]r = [sup.R2][T.sub.P2] x [sup.P2][T.sub.P1] x [sup.P1][T.sub.R1] x [sup.R1]r (1)

* Programming in ACL Language the master robot for linear and circular movement;

* Programming in ACL Language the slave robot for the same movements, but with the values of points coordinates calculated with the equation (1).

* Testing the algorithm for different robot master positions and motions.

* Programming in ACL Language the master robot for automatic downloading the Cartesian coordinates of poses to the PC.

* Conceiving a program (Robot-Robot Cooperation) in Visual Basic environment (Schneider, 1998) for receiving the data from master controller, computing the transformation coordinates and downloading the data to the slave controller. The input data window of the program is presented in figure 3.

* Programming in ACL Language the slave robot for automatic receiving the Cartesian coordinates of poses from the PC.

* Testing the programs.

[FIGURE 3 OMITTED]

[FIGURE 4 OMITTED]

The scheme of the control system is presented in figure 4.

For the full circle motion, there were three poses teach-in, with respect to the master robot world coordinates. The fourth point was calculated in following steps:

* Three points determine a plane. A reference system was attached to this plane.

* The three point coordinates, with respect to the master robot, were transformed with respect to the new reference system. The three points determine a circle.

* The fourth point coordinates were calculated to be on the circle and then transformed with respect to the master robot reference system.

4. CONCLUSION

The motions were programmed only for position, the tool orientation was neglected and it can be a further development task. The ER V+ is more versatile. The robot ER VII was selected to be the master robot, because the motion programming was done on-line. So it can be avoided (minimized) the mechanical blockage of the slave robot arm.

The further development on collaborative robots may include the force and speed control in both master and slave robot controller, motion coordination by a targeted work piece or by a human operator.

5. REFERENCES

Liu, Y.-H., Arimoto, S., Parra-Vega, V., & Kitagaki, K. (1997). Decentralized adaptive control of multiple manipulators in cooperations. International Journal of Control, Volume 67, Number 5, 20 July 1997, pp. 649-674(26)

Nicosia, S. & Tomei, P. (1990). Robot control by using only joint position measurements. Automatic Control, IEEE Transactions on Volume 35, Issue 9, Sep 1990, pp. 1058--1061

Novotny, F. & Horak, M. (2008). Parallel Cooperation of Robots during Handling with Jumbo Glass Sheets. Available from http://www.scientific.net/0-87849-3875/465/ Accessed: 2008-04-15

Rodriguez-Angeles, A., & Nijmeijer, H. (2001). Coordination of two robot manipulators based on position measurements only. International Journal of Control, Volume 74, Number 13, pp. 1311-1323

Schneider, D (1998). An introduction to programming using Visual Basic 6.0, Prentice Hall, ISBN 3-13-936428-5, USA