Remote characterization of high radiation environments is a pressing application area where robots can provide benefits in terms of time, cost, safety and quality of data. However, the DOE roadmap for Robotics and Intelligent Machines states that 'usability' may well prove to be the most challenging and yet crucial component of robotic systems for remote characterization and handling of radioactive and hazardous materials. In 2001, the INEEL successfully deployed a teleoperated robotic system coupled with a Gamma Locating and Isotopic Identification Device (RGL&IID) to characterize an area that had been closed to human entry for many years. This paper examines the human-robot dynamic of this teleoperated task and the limitations inherent to the master-slave strategy employed. Next, the paper outlines an innovative, mixed-initiative command and control architecture developed to address these limitations. The resulting, mixed-initiative control architecture retains the human in the loop, but interleaves multiple levels of human intervention into the functioning of a robotic system that can, in turn, scale its own level of initiative to meet whatever level of input is handed down.
We solve a variation of a classic make‐to‐stock inventory problem introduced by Gavish and Graves. A machine is dedicated to a single product whose demand follows a stationary Poisson distribution. When the machine is on, items are produced one at a time at a fixed rate and placed into finished‐goods inventory until they are sold. In addition, there is an expense for setting up the machine to begin a production run. Our departure from Gavish and Graves involves the handling of unsatisfied demand. Gavish and Graves assumed it is backordered, while we assume it is lost, with a unit penalty for each lost sale. We obtain an optimal solution, which involves a produce‐up‐to policy, and prove that the expected time‐average cost function, which we derive explicitly, is quasi‐convex separately in both the produce‐up‐to inventory level Q and the trigger level R that signals a setup for production. Our search over the (Q, R) array begins by finding Q0, the minimizing value of Q for R = 0. Total computation to solve the overall problem, measured in arithmetic operations, is quadratic in Q0. At most 3 Q0 cost function evaluations are required. In addition, we derive closed‐form expressions for the objective function of two related problems: one involving make‐to‐order production and another for control of an N‐policy M/D/1 finite queue. Finally, we explore the possibility of solving the lost sales problem by applying the Gavish and Graves algorithm for the backorder problem.
Remote characierizarion of high radiarion environments is a pressing application area where robois have the potential ro provide benefits in rems of time, cost, safety and quality of darn. However, the ability ro design robots that can be used effecrively has proven ro be no easy task. In 2001, the Idaho Narional Engineering and Environmental Laboratory (INEEL) successfilly deployed a releoperated roboiic system coupled wirh a Gamma .Locating and Isotopic Identification Device (RGL&llD) io characterize an area that had been closed ro human entry for many years. This paper examines the limiiations to the conirol sirategy used and discusses how current efforts ar rhe INEEL are developing intelligent controls rhat can acrively mediate between the human and the roboric elements of the sysiem. The resulting, mixed-initiative conrrol archirecrure allows the user to shift the level of roboi initiative throughout the task as needed. This sysiem offers rhe opporruniry for rhe human and robor ro become a team where each can suppon the capabilities and limiiaiions of rhe other.
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