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The problem of production control for a hybrid manufacturing/remanufacturing system under uncertainties is analyzed. Two sources of uncertainties are considered: machines random breakdowns and repairs are modeled as a Poisson process, and demand level variations are modeled as a diffusion type process. The solution to optimal control problem is determined numerically by solving the Hamilton-Jacobi-Bellman (HJB) equations which are shown to be second order partial differential equations (PDEs). The optimal policy for manufacturing is of hedging-point type, while for remanufacturing it is a three-value function. We illustrate obtained results by simulation examples and analyze how the optimal production policy and optimal cost evolve while the statistical characteristics of the random demand vary.

This paper presents the problem of navigation, gate recognition, and gate crossing for a real size outdoor mobile robot. The vehicle localization and general navigation is based on Global Positioning System (GPS) and Inertial Navigation System (INS). These sensors are aided by a Laser Measuring System (LMS). The laser scanner sensor gives information about the gate exact location, its shape, and vehicle attitude with respect to the gate. This necessitates the transition from GPS/INS based guidance in the open field to the range based, guidance system in proximity of the gate. A recognition procedure based on the concept of the gate signature has been developed and shown. It is followed by novel map-matching and localization procedures respectively. The developed navigation controller makes use of the polar coordinate representation and discontinuous feedback adapted for real time applications.

For a robot to be autonomous, it needs to build a representation of its environment and to locate itself. When exploring new environments, localization and map-building processes are actually coupled. Closing the loops is a challenging aspect for existing map-building methods — they are often time consuming and hardly usable for real-time applications. This paper presents a method that allows multi-loop closing by separating map building process into local and global mapping. Our method is based on the segmentation of the whole environment into “corridors” and “intersections”. The latter are used as natural landmarks: they are recognized when the robot passes second time through an already visited area. Local maps of each corridor and intersection are integrated into the global map which is updated after loop closing event. As proposed recalculations of the whole map are relatively simple, the process can be effectively used for real time applications.

This paper describes an approach to the coordination of two car-like robots that must cooperate in accomplishing a transportation task, namely carrying a long beam that neither one can carry alone. The robots are not allowed any form of explicit exchange of information, and can therefore only "communicate" through the task that they perform together. We propose for this problem a decentralized controller that relies on a two-stage strategy. At the higher level, each robot computes, based on the information available to it, a desirable motion for the beam. The lower-level controller must then generate controls to be fed to the robot's actuators (its steering and propulsion motors), so that the beam's actual motion approximates as well as possible the desired one. This article presents our mathematical formalism and the derivation of the corresponding control laws. We present the results of simulation runs of this decentralized, two-level control strategy, as well as the experimental testbed built for studying such coordination tasks.