ATEX & hazardous areas T
he decommissioning of nuclear facilities poses major challenges for operators. Whether decommissioning or safe containment, the amount of nuclear waste to be disposed
of is growing at an overwhelming rate worldwide. Automation is increasingly required to handle nuclear waste, but the nuclear industry is reluctant of fully autonomous robotic control methods for safety reasons, and remote-controlled industrial robots are preferred in hazardous environments. However, such complex tasks as remote-controlled gripping or cutting of unknown objects with the help of joysticks and video surveillance cameras are difficult to control and sometimes even impossible. To simplify this process, the National Centre for Nuclear Robotics led by the Extreme Robotics Lab at the University of Birmingham in the UK is researching automated handling options for nuclear waste. The robot assistance system developed there enables “shared” control to perform complex manipulation tasks by means of haptic feedback and vision information provided by Ensenso 3D camera. The operator, who is always present in the loop can retain control over the robot’s automated actions, in case of system failures.
THE APPLICATION
Anyone who has ever tried out a fairground grab machine can confirm it: Manual control of grab arms is anything but trivial. As harmless as it is to fail when trying to grab a stuffed bunny, failed attempts can be as dramatic when handling radioactive
HANDLE WITH CARE
A robot-assisted system with Ensenso 3D camera is enabling the safe handling of nuclear waste...
waste. To avoid damage with serious consequences for humans and the environment, the robot must be able to detect the radioactive objects in the scene extremely accurately and act with precision. The operator literally has it in his hands, it is up to him to identify the correct gripping positions. At the same time, he must correctly assess the inverse kinematics (backward transformation) and correctly determine the joint angles of the robot’s arm elements in order to position it correctly and avoid collisions. The assistance system developed by the British researchers simplifies and speeds up this task immensely: with a standard industrial robot equipped with a parallel jaw gripper and an Ensenso N35 3D camera.
The system autonomously scans unknown waste objects and creates a 3D model of them in the form of a point cloud. This is
extremely precise because Ensenso 3D cameras work according to the principle of
Dr Naresh Marturi, senior research scientist in robotics (left), Maxime Adjigble, robotics research engineer (right)
spatial vision (stereo vision), which is modelled on human vision. Two cameras view the object from different positions. Although the image content of both camera images appear identical, they show differences in the position of the objects viewed. Since the distance and viewing angle of the cameras as well as the focal length of the optics are known, the Ensenso software can determine the 3D coordination of the object point for each individual image pixel. In this case, the scene is captured using different scanning positions of the camera and combined to get a complete 3D surface from all viewing angles. Ensenso’s calibration routines help transform the individual point clouds into a global coordinate system, which improves the complete virtual image. The resulting point cloud thus contains all the spatial object information needed to communicate the correct gripping or cutting position to the robot.
With the help of the software, the Enseno 3D camera takes over the perception and evaluation of the depth information for the operator, whose cognitive load is considerably reduced as a result. The assistance system combines the haptic features of the object to be gripped with a special gripping algorithm. “The scene cloud is used by our system to automatically generate several stable
66 February 2023 Instrumentation Monthly
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