Publications

Abstract not provided.

Perhaps the most basic barrier to the widespread deployment of remote manipulators is that they are very difficult to use. Remote manual operations are fatiguing and tedious, while fully autonomous systems are seldom able to function in changing and unstructured environments. An alternative approach to these extremes is to exploit computer control while leaving the operator in the loop to take advantage of the operator's perceptual and decision-making capabilities. This report describes research that is enabling gradual introduction of computer control and decision making into operator-supervised robotic manipulation systems, and its integration on a commercially available, manually controlled mobile manipulator.

Umbra is a new Sandia-developed modeling and simulation framework. The Umbra framework allows users to quickly build models and simulations for intelligent system development, analysis, experimentation, and control and supports tradeoff analyses of complex robotic systems, device, and component concepts. Umbra links together heterogeneous collections of modeling tools. The models in Umbra include 3D geometry and physics models of robots, devices and their environments. Model components can be built with varying levels of fidelity and readily switched to allow models built with low fidelity for conceptual analysis to be gradually converted to high fidelity models for later phase detailed analysis. Within control environments, the models can be readily replaced with actual control elements. This paper describes Umbra at a functional level and describes issues that Sandia uses Umbra to address.

The direct connection of information, captured in forms such as CAD databases, to the factory floor is enabling a revolution in manufacturing. Rapid response to very dynamic market conditions is becoming the norm rather than the exception. In order to provide economical rapid fabrication of small numbers of variable products, one must design with manufacturing constraints in mind. In addition, flexible manufacturing systems must be programmed automatically to reduce the time for product change over in the factory and eliminate human errors. Sensor based machine control is needed to adapt idealized, model based machine programs to uncontrolled variables such as the condition of raw materials and fabrication tolerances.

Need-based cross cutting technology is being developed which is broadly applicable to the clean up of hazardous and radioactive waste within the US Department of Energy`s complex. Highly modular, reusable technologies which plug into integrated system architectures to meet specific robotic needs result from this research. In addition, advanced technologies which significantly extend current capabilities such as automated planning and sensor-based control in unstructured environments for remote system operation are also being developed and rapidly integrated into operating systems.

This paper describes Virtual Collaborative Environments (VCEs), an information architecture that enables remote sharing of mechatronic (intelligent electrochemical devices) resources. This architecture will leverage the proposed National Information Infrastructure (NII) or Information Highway to share valuable resources and reduce product-to-market cycles. Benefits of sharing mechatronic resources with VCEs are explored. An existing prototype VCE is described and experimental and illustrative results from using the prototype VCE system are discussed.

Hazardous operations which in the past have been completed by technicians are under increased scrutiny due to high costs and low productivity associated with providing protective clothing and environments. As a result, remote systems are needed to accomplish many hazardous materials handling tasks such as the clean up of waste sites in which the exposure of personnel to radiation, chemical, explosive, and other hazardous constituents is unacceptable. Traditional remote operations have proven to have very low productivity when compared with unencumbered humans. Computer models augmented by sensing and structured, modular computing environments are proving to be effective in automating many unstructured hazardous tasks.

The US Department Energy`s Office of Technology Development has sponsored the development of generic robotics technologies for application to a wide range of remote systems. Of primary interest is the development of technologies which enable faster, safer, and cheaper cleanup of hazardous waste sites than is possible using conventional human contact or remote manual approaches. The development of model-based sensor-directed robot control approaches supports these goals by developing modular control technologies which reduce the time and cost of development by allowing reuse of control system software. In addition, the use of computer models improves the safety of remote site cleanup by allowing automated errors detection and recovery while reducing the time for technology development.

Remote systems are needed to accomplish many tasks such as the clean up of waste sites in which the exposure of personnel to radiation, chemical, explosive, and other hazardous constituents is unacceptable. In addition, hazardous operations which in the past have been completed by technicians are under increased scrutiny due to high costs and low productivity associated with providing protective clothing and environments. Traditional remote operations have, unfortunately, proven to also have very low productivity when compare with unencumbered human operators. However, recent advances in the integration of sensors and computing into the control of conventional remotely operated industrial equipment has shown great promise for providing systems capable of solving difficult problems.

Hazardous operations which in the past have been completed by technicians are under increased scrutiny due to high costs and low productivity associated with providing protective clothing and environments. As a result, remote systems are needed to accomplish many hazardous materials handling tasks such as the clean up of waste sites in which the exposure of personnel to radiation, chemical, explosive, and other hazardous constituents is unacceptable. Traditional remote manual operations have proven to have very low productivity when compared with unencumbered humans. Computer models augmented by sensing and structured, modular computing environments are proving to be effective in automating many unstructured hazardous tasks.

The US Department of Energy`s Office of Technology Development (OTD) has sponsored the development of the Generic Intelligent System Controller (GISC) for application to remote system control. Of primary interest to the OTD is the development of technologies which result in faster, safer, and cheaper cleanup of hazardous waste sites than possible using conventional approaches. The objective of the GISC development project is to support these goals by developing a modular robotics control approach which reduces the time and cost of development by allowing reuse of control system software and uses computer models to improve the safety of remote site cleanup while reducing the time and life cycle costs.

This paper discusses a new telerobotic control concept which couples human supervisory commands with computer reasoning. The control system is responsive and accomplishes an operator's commands while providing obstacle avoidance and stable controlled interactions with the environment in the presence of communication time delays. This provides a system which not only assists the operator in accomplishing tasks but modifies inappropriate operator commands which can result in safety hazards and/or equipment damage. Research and development of this concept is being carried out in the Telerobotics Research Laboratory at Sandia National Laboratories. 12 refs., 4 figs.