Publications

This report summarizes the accomplishments of the Laboratory Directed Research and Development (LDRD) project 26546 at Sandia, during the period FY01 through FY03. The project team visited four DoD depots that support extensive aircraft maintenance in order to understand critical needs for automation, and to identify maintenance processes for potential automation or integration opportunities. From the visits, the team identified technology needs and application issues, as well as non-technical drivers that influence the application of automation in depot maintenance of aircraft. Software tools for automation facility design analysis were developed, improved, extended, and integrated to encompass greater breadth for eventual application as a generalized design tool. The design tools for automated path planning and path generation have been enhanced to incorporate those complex robot systems with redundant joint configurations, which are likely candidate designs for a complex aircraft maintenance facility. A prototype force-controlled actively compliant end-effector was designed and developed based on a parallel kinematic mechanism design. This device was developed for demonstration of surface finishing, one of many in-contact operations performed during aircraft maintenance. This end-effector tool was positioned along the workpiece by a robot manipulator, programmed for operation by the automated planning tools integrated for this project. Together, the hardware and software tools demonstrate many of the technologies required for flexible automation in a maintenance facility.

An automated system is described for the sensor-based precision docking and manipulation of large objects. Past work in the remote handling of large nuclear waste containers is extendable to the problems associated with the handling of large objects such as steel coils. Computer vision and ultrasonic proximity sensing are used to control the precision docking of large objects, and swing-damped motion control of overhead cranes is used to control the position of the pickup device and suspended payload during movement. Real-time sensor processing and model-based control are used to accurately position payloads.

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.

Robotic systems are being developed by the Intelligent Systems and Robotics Center at Sandia National Laboratories to perform automated handling tasks with radioactive nuclear materials. These systems will reduce the occupational radiation exposure to workers by automating operations which are currently performed manually. Because the robotic systems will handle material that is both hazardous and valuable, the safety of the operations is of utmost importance; assurance must be given that personnel will not be harmed and that the materials and environment will be protected. These safety requirements are met by designing safety features into the system using a layered approach. Several levels of mechanical, electrical, and software safety prevent unsafe conditions from generating a hazard, and bring the system to a safe state should an unexpected situation arise. The system safety features include the use of industrial robot standards, commercial robot systems, commercial and custom tooling, mechanical safety interlocks, advanced sensor systems, control and configuration checks, and redundant control schemes. The effectiveness of the safety features in satisfying the safety requirements is verified using a Failure Modes and Effects Analysis. This technique can point out areas of weakness in the safety design as well as areas where unnecessary redundancy may reduce the system reliability.

Environmental and operator safety concerns are leading to the elimination of trichloroethylene (TCE) and chlorofluorocarbon (CFC) solvents in electronic component cleaning processes that remove rosin flux, organic and inorganic contamination, and particulates. Present processes depend heavily on these solvents for manual spray cleaning of small components and subassemblies. Use of alternative solvent systems can lead to longer processing times and reduced quality. Automated spray cleaning can improve the quality of the cleaning process, thus enabling the productive use of environmentally conscious materials, while minimizing personnel exposure to hazardous materials. In addition, the use of robotic and automated systems can reduce the manual handling of parts that necessitates additional cleaning. We describe the development of a prototype robotic system for cleaning electronic components in a spray cleaning workcell. An important feature of the prototype system is the capability to generate the robot paths and motions automatically from the CAD models of the part to be cleaned, and to embed cleaning process knowledge into the automatically programmed operations.

A sensor-based intelligent control system is described that utilizes a multiple degree-of-freedom robotic system for the automated remote manipulation and precision docking of large payloads such as waste canisters. Computer vision and ultrasonic proximity sensing are used to control the automated precision docking of a large object with a passive target cavity. Real-time sensor processing and model-based analysis are used to control payload position to a precision of {plus_minus} 0.5 millimeter.

Detailed geometric models have been used within a graphical simulation environment to study transportation cask facility design and to perform design and analyses of robotic systems for handling of nuclear waste. The models form the basis for a robot control environment which provides safety, flexibility, and reliability for operations which span the spectrum from autonomous control to tasks requiring direct human intervention.