An automated system is being developed for handling large payloads of radioactive nuclear materials in an analytical laboratory. The automation system performs unpacking and repacking of payloads from shipping and storage containers, and delivery of the payloads to the stations in the laboratory. The system uses machine vision and force/torque sensing to provide sensor-based control of the automation system in order to enhance system safety, flexibility, and robustness, and achieve easy remote operation. The automation system also controls the operation of the laboratory measurement systems and the coordination of them with the robotic system. Particular attention has been given to system design features and analytical methods that provide an enhanced level of operational safety. Independent mechanical gripper interlock and tool release mechanisms were designed to prevent payload mishandling. An extensive failure modes and effects analysis of the automation system was developed as a safety design analysis tool.

Experimental investigations into the application of intelligent robot control technology to the problem of removing waste stored in tanks are described. The authors discuss the experimental environment employed, with particular attention to the computing and software control environment. Intelligent system control is achieved through the integration of extensive geometric and kinematic world models with real-time sensor-based control. All operator interactions with the system are through fully animated, graphical representations which validate all operator commands before execution to provide for safe operation. Sensing is used to add information to the robot system's world model and to allow sensor-based servo control during selected operations. Initial test results are reported, and the potential for applying advanced intelligent control concepts to the removal of waste in storage tanks is discussed.>