# Sensor-Guided Assembly of Segmented Structures with Industrial Robots
## 5 Testbed and Hardware  
The experimental testbed shown in Figure 1 is designed to approximate a real factory environment. The testbed contains an ABB IRB-6640 robot equipped with a 6-suction-cup vacuum gripper. The gripper is mounted with an ATI F/T sensor, two cameras, a dimmable light, and three pairs of pressure sensors used to monitor the engagement of the suction cups to the panel. There is also an overhead camera over the pick-up area. There are two different types of panels, representing root (thicker) and mid-section portions of the structure. Each panel weighs approximately 35 kg. The robot has a payload capacity of 180 kg, 0.07 mm position repeatability, and 0.7 mm path repeatability. The robot controller supports the external guided motion (EGM) mode for joint motion command and joint angle access at a rate of 4 ms. A six-axis F/T sensor Omega160 from ATI Corp. is mounted at the center of the end effector. The sampling rate is up to 7 KHz.  
A FLIR Vision camera, the Blackfly S Color 20.0 (5472 \(\times\) 3648) MP USB3 Vision, is placed overhead above the pick-up nest. Using a Computar 1.1\({}^{\prime\prime}\) 12 mm f/2.8 12 MP ultra low distortion lens, the estimated field of view from 3.2 m is 3.768 m \(\times\) 2.826 m, and hence each pixel is approximately 1.15 mm/pixel \(\times\) 1.28 mm/pixel in the target area (the lens decreases the resolution by 40%). This camera is used to locate the panel at the pickup nest for the initial pickup, requiring a bigger field of view and coarser localization. Two FLIR Vision Blackfly S Color 5.0 (2448 \(\times\) 2048) MP USB3 Vision cameras are mounted at one end of the gripper. Using a Tamron 1.1\({}^{\prime\prime}\) 8 mm f/1.8 12 MP fixed focal lens, the estimated field of view from 0.5 m distance is 0.88 m \(\times\) 0.66 m; hence the resolution is 0.36 mm/pixel \(\times\) 0.32 mm/pixel in the target area. The gripper cameras move with the end effector at an offset distance, and 10-m active USB3 extension cables from Newne (FireNEXAMAF10M) ensure that the camera data are reliably transmitted without attenuation from the long distance. In this paper, we only use one camera on the gripper for PBVS.  
After the panel is picked up and moved above the assembly nest, the gripper camera, which only has a small portion of view blocked by the panel, localizes the assembly nest with respect to the panel with fine resolution for placement. We use a precisely manufactured checkerboard with a 30 mm \(\times\) 30 mm grid to calibrate the high resolution cameras, resulting in a re-projection error of 0.13 pixels. To accurately detect, identify and localize objects in the image frame, we selected an open source Augmented Reality (AR) library based on OpenCV, called ArUco markers. The 3D position and orientation of each marker can be quickly extracted from a single camera viewpoint. The markers are printed using a 600 dpi resolution printer on vinyl paper and attached to flat acrylic boards in order  
Figure 5: The ROS software architecture implements the entire process, including user interface, motion planning (using Tesseract), vision service and object recognition, robot kinematic control, and robot interface.  
to minimize errors. We combined multiple markers as shown in Figure 6 onto a marker board for higher accuracy localization. The marker size is arbitrarily determined as long as it can be visible to the cameras. The marker pose is determined to avoid contacting the suction cups during pickup and placement. Note that the markers are allowed to laser inked on the panels in the real factory, and the concept applies to other 3D pose estimation methods using features or edges directly from the panel. Based on this setup, the gripper camera accuracy is [0.26, 0.19, 1.46] mm in the camera \((x,y,z)\) directions. We are mainly concerned about the \((x,y)\) accuracy, since compliance control addresses the \(z\)-direction motion.