The 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 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 an Ensenso 3D camera from IDS Imaging Development Systems. The operator, who is always present in the loop can retain control over the robot’s automated actions, in case of system failures.
Anyone who has ever tried out a fairground grab machine can confirm it: the 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 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.
Image: IDS.
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 spatial vision (stereo vision), which is modelled on human vision. 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 gripping positions. Based on this, our ‘hypothesis ranking algorithm’ determines the next object to pick up, based on the robot’s current position”, explains Dr Naresh Marturi, Senior Research Scientist at the National Centre for Nuclear Robotics.
Read the complete case study and find more information about IDS on its website.
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