This article describes the concepts and strategies that have guided the design and implementation of this simulator, with emphasis on those features that are particularly relevant to its most efficient use. 1.1 The problem domain

and maintenance. The design and development costs for detailed simulation models for complex systems can easily rival the costs for the physical systems themselves. The simulation environment we developed at UCLA attempts to address some of these issues by providing these features: . An easy path

During development of new protocols and systems researchers in most cases use simulations for evaluation of their product, especially in the area of communication networks. The quality of the simulation environment, however, significantly influences the quality of a product’s evaluation. Therefore

A digital computer is generally believed to be an efficient universal computing device; that is, it is believed able to simulate any physical computing device with an increase in computation time of at most a polynomial factor. This may not be true when quantum mechanics is taken into consideration

Ptolemy is an environment for simulation and prototyping of heterogeneous systems. It uses modern object-oriented software technology (C++) to model each subsystem in a natural and efficient manner, and to integrate these subsystems into a whole. Ptolemy encompasses practically all aspects

Three experimental environments traditionally support network and distributed systems research: network emulators, network simulators, and live networks. The continued use of multiple approaches highlights both the value and inadequacy of each. Netbed, a descendant of Emulab, provides

on an Internet testbed and via large-scale network simulation. The results show that SplitStreamd istributes the forward ing load among all peers and can accommod'9 peers with different band0 d capacities while imposing low overhead for forest constructionand maintenance.

Information sharing is a key requirement in Live, Virtual, and Constructive (LVC) simulation environ-ments. Operational plans, orders, and requests from live, virtual, or constructive command and control systems or simulations need to be received by and operated on by receiving LVC systems

cockpit interface Abstract cockpit interface Abstract cockpit interface Abstract cockpit interface Figure 1: Human and automated pilots interact with the DIS environment via distributed simulators.

A robot exploring an unknown environmentmay need to build a world model from sensor measurements. In order to integrate all the frames of sensor data, it is essential to align the data properly. An incremental approach has been typically used in the past, in which each local frame of data is aligned to a cumulative global model, and then merged to the model. Because different parts of the model are updated independently while there are errors in the registration, such an approachmay result in an inconsistent model. In this paper, we study the problem of consistent registration of multiple frames of measurements (range scans), together with the related issues of representation and manipulation of spatial uncertainties. Our approachistomaintain all the local frames of data as well as the relative spatial relationships between local frames. These spatial relationships are modeled as random variables and are derived from matching pairwise scans or from odometry. Then we formulat...