Both Korean and UK nuclear industries share the same challenge of accessing large radio-chemical process environments to perform remote intervention tasks. In particular, both UK and Korea have identified a significant need for unmanned systems which can handle and retrieve contaminated materials in zones which are too hazardous to risk manned entries.
This project will directly address this need by developing novel robotic systems which can enter, monitor, and carry out manipulative actions on a wide variety of objects and materials in nuclear decommissioning environments, which would otherwise remain inaccessible and unmanageable.
The UoB-KAERI-NNL consortium will develop hardware, software, algorithms and control methods for a mobile robot manipulator, comprising an unmanned vehicle equipped with an arm and end-effectors (which could include hands and-or cutting devices), which can enter hazardous environments, perform a wide variety of manipulation tasks on materials inside those environments, and retrieve objects from the environment in a controlled fashion.
Additionally, we will develop a smaller "child" pipe-climbing robot, which can ride on the mother vehicle and be deployed onto pipe-work (prevalent in many nuclear installations) via the mother vehicle's manipulator arm. The purpose of the child robot is to inspect zones which would otherwise be inaccessible in highly complex and 3D nuclear plant environments, for example to reach places that are high, narrow or cluttered. Additionally, cameras mounted on the child robot can provide useful alternative views of the mother-vehicle, facilitating autonomous "visual-servoing" control of the manipulator arm, and/or better tele-operative control by an expert human operator.
The control approach will be one of "semi-autonomy", "tele-autonomy" or "variable-autonomy" which would therefore go beyond what has previously been attempted in nuclear environments. Traditionally, safety-critical industries have been very conservative about allowing the devolution of control from human operator to an autonomous machine, and have instead relied on direct tele-operation (e.g. a human controlling each joint of a robot arm by means of switches or joy-sticks). However, it is becoming increasingly clear that the combination of i) the vast scale of the decommissioning task, and ii) the complexity and high degrees-of-freedom of the robots needed to perform decommissioning, means that certain kinds of autonomous control will be required as "operator-assistance" technologies. For example, a human operator should be able to mouse-click on an object, and have the robot autonomously grasp it, rather than the human attempting to control two or more mobile base motors, six or more arm motors and two or more gripper fingers directly.
Additionally, autonomous sensing approaches, such as 3D reconstruction of environments by computational vision, will be necessary for both situational awareness of the remote human operator, and automatic planning and control algorithms running on the robot. We will develop advanced computer vision and path-planning algorithms, which will enable collision-free navigation of the robot vehicle, and successful autonomous arm and hand trajectories to effect robust grasps on arbitrarily shaped objects and materials.
Furthermore, we will develop advanced dynamics models and control methods to facilitate highly dynamic robot actions, such as braciation or swinging of the climbing child robot, or forceful actions of the mother mobile-maniplator with respect to contacts with its environment, for example cutting and grinding of objects, or dragging of grasped objects.
The overall aim is to enable the safe, unmanned retrieval of contaminated materials from hazardous zones.
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