**4.1 High-speed vision system with newly developed vision chip**

Besides the method of realizing a high-speed vision system with traditional configuration as shown in **Figure 5(a)**, new high-speed vision system (**Figure 5(b)**)

**Figure 7.** *Experimental setup for contour tracing task.*

*Dynamic Compensation Framework to Improve the Autonomy of Industrial Robots DOI: http://dx.doi.org/10.5772/intechopen.90169*

with newly developed vision chip is introduced. The new vision chip combines high-frame-rate imaging and highly parallel signal processing with high-resolution, high-sensitivity, low-power consumption [26]. The 1/3.2-inch 1.27 Mpixel 500 fps (0.31 Mpixel 1000 fps 2 2 binning) vision chip is fabricated with 3D-stacked column-parallel analog-to-digital converters (ADCs) and 140 giga-operations per second (GOPS) programmable single instruction multiple data (SIMD) columnparallel processing elements (PEs) for high-speed spatiotemporal image processing. The programmable PE can implement high-speed spatiotemporal filtering and enables imaging and various image processing such as target detection, recognition, and tracking on one chip. By realizing image processing on the chip, it can suppress power consumption to maximum 363 mW at 1000 fps. Comparing with conventional high-speed vision system, the new high-speed vision system will greatly save space and energy and is very suitable for compact usage in robotic applications. The high-speed vision was configured to work at 1000 fps with a resolution of 648 484. Overall latency of high-speed visual feedback was measured to be within 3.0 ms [25].

### **4.2 Add-on compensation module with two DOFs**

In order to accompany with the parallel-link robot to realize the twodimensional contour tracing task, an add-on module prototype capable of realizing fine compensation in two dimensions was developed. The add-on module was with two orthogonal linear joints, and specifications for the actuators of the module were estimated by an accelerometer and are shown in **Table 2**. The total weight of the module was about 0.27 kg. The high-speed vision was configured on the moving table of the add-on module, and the tracing task was implemented in such a manner that the high-speed vision was guided to travel along the curve with the curve's center accurately aligned with the center (324,242) of the high-speed vision's images.

### **4.3 Coarse motion planning of industrial robot**

The same as the peg-and-hole alignment task, the main robot's motion was planned using vision information from the globally configured VGA camera. The implementation involved exactly the same with the last task: a rough calibration and image processing to extract key points (via-points) of a target contour path considering the limited working range of the add-on module. Extraction of key points of a target contour was implemented in the following manner [25]:



**Table 2.**

*Spec. of actuators for the two-DOF add-on module prototype.*

fine alignment within 0.2 s within an accuracy of 0.1 mm. For 20 trials with different positions of the workpiece, all alignments were satisfactory as the proper insertions were observed [13]. A video for the peg-and-hole alignment task can be

**4. Application scenario 2: contour tracing in two dimensions**

the motion planning for the main robot's coarse positioning.

**4.1 High-speed vision system with newly developed vision chip**

Besides the method of realizing a high-speed vision system with traditional configuration as shown in **Figure 5(a)**, new high-speed vision system (**Figure 5(b)**)

The contour tracing task was conducted to verify the proposed method in realizing fast and accurate trajectory motion control under internal and external uncertainties [25]. Robotic contour tracing (contour following) is a useful technique in manufacturing tasks such as welding and sealing. Fast and accurate contour tracing under uncertainty from both a robot system and external environment is quite challenging. In this study, the task was confined in two dimensions. The experimental testbed is shown in **Figure 7**. The target is a closed curve with irregular contour pattern (2.5 mm width) printed on a paper which is placed on a stage. External disturbance is exerted on the stage to simulate environmental uncertainty. The same parallel-link robot was deployed as the main robot to execute the fast, coarse global motion. A two-DOF compensation module was configured at the end effector of the main robot. The same VGA camera was globally configured to realize

found on the website [24].

*Industrial Robotics - New Paradigms*

**Figure 7.**

**72**

*Experimental setup for contour tracing task.*

intended to perform contour tracing with a constant speed of the main robot. Therefore the smooth path (100%) method was adopted to control the main robot. However, this introduced additional source of uncertainty to the main robot's tra-

Before each experiment, the paper with irregular contour pattern (2.5 mm width) printed on it was placed randomly on the working stage. Key points (shown in **Figure 8(b)**) for coarse tracing motion of the parallel-link robot were extracted. The parallel-link robot was set to be 100% smooth motion with 400 mm/s speed. Along with the coarse tracing by the parallel-link robot, the compensation module was realizing fine local compensation in two dimensions with the visual feedback

*Result of contour tracing [25]. (a) Image profile of contour tracing without external disturbance. (b) Image*

*profile of contour tracing with random external disturbance.*

jectory. One case of the extracted key points is shown in **Figure 8(b)**.

*Dynamic Compensation Framework to Improve the Autonomy of Industrial Robots*

information from the new high-speed vision system.

**4.4 Experimental result**

*DOI: http://dx.doi.org/10.5772/intechopen.90169*

**Figure 9.**

**75**

**Figure 8.**

*Coarse motion of the main robot. (a) Method for extraction of key points. (b) Extracted key points.*

3.Point *pi* starting from *pc* along the extraction direction with a small step size *δ* was examined. If its distance to chord *pcpd* ! was within the work range (*Smax*) of the compensation module in image space, we then continue to examine the next point by increasing one step further. Otherwise, *pi* was elected as the new extraction point *pn*. With insertion of the new point *pn*, points between *pc* and *pn* should be re-examined to see whether distance from *pj* to chord *pcpn* ! was bigger than *Smax* or not. If it was true, another new extraction point at *pj* should be inserted, and a recursive check for points between *pc* and *pj* should be conducted. Until all points between *pc* and *pn* were secured (the distance from each point to the corresponding chord was smaller than *Smax*), move the probing circle by updating *pc* with *pn*. And then the algorithm will return back to the last step until all the discretization points of the target contour were visited. The distance from *pi* to chord *pcpd* ! was represented as *D* and was calculated by

$$D = \frac{|\overrightarrow{p\_c}\overrightarrow{p\_i} \times \overrightarrow{p\_c}\overrightarrow{p\_d}|}{|\overrightarrow{p\_c}\overrightarrow{p\_d}|}\tag{12}$$

4.Points *p*0, *p*1, … , *pn* were the key points extracted from the target contour.

Usually, a commercial robot controller enables different methods of on-line path generation with selected key points. As an example, as shown in **Figure 8(a)**, a point-to-point (P2P) method that generated a path strictly passing through all key points with nonconstant velocity was included. On the other hand, a smooth path (100% smoothing factor) method would achieve a constant velocity profile while at the same time the exact generated trajectory would be not known to the user in advance. In many industrial applications, contour tracing with constant speed has significant advantages. It not only achieves good energy efficiency by reducing unnecessary acceleration and deceleration but also obtains better working performance in cases where work timing is critical, such as in welding. In this task, we

*Dynamic Compensation Framework to Improve the Autonomy of Industrial Robots DOI: http://dx.doi.org/10.5772/intechopen.90169*

intended to perform contour tracing with a constant speed of the main robot. Therefore the smooth path (100%) method was adopted to control the main robot. However, this introduced additional source of uncertainty to the main robot's trajectory. One case of the extracted key points is shown in **Figure 8(b)**.
