The integration of multiple solid state LiDARs could achieve similar performance as a spinning LiDAR, by focusing on the dedicated area of interests. However, due to their small FoV settings, it is either required to rely on external sensors or form FoV overlaps to calibrate the extrinsic parameters between multiple LiDAR units. To overcome such limitations, we develop a targetless calibration method, which creates FoV overlaps (hence co-visible features) through movements and constructs a factor graph to resolve the constraints between LiDAR poses and extrinsic parameters. By solving the formulated problem with graph optimization, our proposed method could calibrate the extrinsic of LiDARs with few or even no overlapped FoVs, meanwhile, produce a globally consistent point cloud map. Experiments on different sensor setups and scenes have demonstrated the accuracy and robustness of our proposed approach.

Extrinsic Calibration of Multiple LiDARs of Small FoV in Targetless Environments

With 3D sensing becoming cheaper, environment-aware and visually-guided robot arms capable of safely working in collaboration with humans will become common. However, a reliable calibration is needed, both for camera internal calibration, as well as Eye-to-Hand calibration, to make sure the whole system functions correctly. We present a framework, using a novel combination of well proven methods, allowing a quick automatic calibration for the integration of systems consisting of the robot and a varying number of 3D cameras by using a standard checkerboard calibration grid. Our approach allows a quick camera-to-robot recalibration after any changes to the setup, for example when cameras or robot have been repositioned. Modular design of the system ensures flexibility regarding a number of sensors used as well as different hardware choices. The framework has been proven to work by practical experiments to analyze the quality of the calibration versus the number of positions of the checkerboard used for each of the calibration procedures.

/pdf/automatic-calibration-of-a-robot-manipulator-and-multi-3d-43ravz8asu.pdf

Automatic calibration of a robot manipulator and multi 3D camera system

The automatic deburring process of casting parts has been commonly investigated by industrial robot manipulators in recent decade. Majority of solutions are dependent on human teaching or robot Off-Line Programming system (OLP), which assume that deburring paths are completely predefined offline and have a perfect relative calibration between the workpiece and robot. Those limiting assumptions lack practical applications in uncertainty as diverse as modeling error, robot positioning error and environment. In this paper, we consider the method of automatic deburring process with visual assistance for synchronously detecting the deburring path and compensating calibration error. To do so, a deburring system which consists of two interconnected modules is presented, including the detection and extraction of deburring paths using a industrial CCD camera, and a self-developed OLP system (RobSim) is applied to generate robot executable trajectories with the presence of limited visual data. Our deburring system that has the automatic deburring capability depends on the ability to have a good insight of the workpiece and environment. An industrial application is considered to verify the feasibleness and effectiveness of our system. Experimental results show that the improvement of deburring performance by the seamless integration of visual system and the advantages of an OLP system in the field of automatic deburring process.

Integration of Visual Information and Robot Offline Programming System for Improving Automatic Deburring Process

With advancing technologies, robotic manipulators and visual environment sensors are becoming cheaper and more widespread. However, robot control can be still a limiting factor for better adaptation of these technologies. Robotic manipulators are performing very well in structured workspaces, but do not adapt well to unexpected changes, like people entering the workspace. We present a method combining 3D Camera based workspace mapping, and a predictive and reflexive robot manipulator trajectory estimation to allow more efficient and safer operation in dynamic workspaces. In experiments on a real UR5 robot our method has proven to provide shorter and smoother trajectories compared to a reactive trajectory planner in the same conditions. Furthermore, the robot has successfully avoided any contact by initialising the reflexive movement even when an obstacle got unexpectedly close to the robot. The main goal of our work is to make the operation more flexible in unstructured dynamic workspaces and not just avoid obstacles, but also adapt when performing collaborative tasks with humans in the near future.

Multi 3D Camera Mapping for Predictive and Reflexive Robot Manipulator Trajectory Estimation

Since the last decade the demand of CFRP parts is rapidly increasing in the aerospace industry. A trend towards large scale and highly integrated parts manufactured by using dry textiles and vacuum assisted infusion processes is visible. One of the drawbacks of such composites so far is the mechanical performance compared to prepreg material. The complexity of the manufacturing process chain requires decent knowledge about the dependencies within each single step. Contactless Lock-In Thermography offers the observation of large scale parts at various stages along the process chain. The approach at DLR Augsburg of a robot based measuring system for industrial applications has been presented in previous papers. With this paper DLR-Center for Lightweight-Production-Technology in Augsburg will give insight into current work and results derived from first experiments.

/pdf/cfrp-manufacturing-process-chain-observation-by-means-of-1xumxplu5w.pdf

CFRP manufacturing process chain observation by means of automated thermography

Hand-Eye Calibration

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