Reduction of risks and acquisition delays is a major issue for procurement services, as it contributes directly to the cost and availability of the system. A new approach, know as simulation-based acquisition (SBA) has been used increasingly within the last past years. In this paper, we address cost-effectiveness issues of SBA. Using the standard cost estimates familiar to program managers, we show first that the cost overhead of using SBA instead of a “conservative” approach is cancelled and turned into a financial gain as soon as the first unforeseen event arises. Then, we show that reuse within SBA of a system-of-systems induces financial gains which give the design of the encompassing meta-system for free.
We present an intelligent sensor, consisting in 2 CCDs with different field of view sharing the same optical motion, which can be controlled independently or not in their horizontal, vertical and rotational axis, and are connected in a closed loop to image processing resources. The goal of such a sensor is to be a testbed of image processing algorithms in real conditions. It illustrates the active perception paradigm and is used for autonomous navigation and target detection/tracking missions. Such a sensor has to meet many requirements : it is designed to be easily mounted on a standard tracked or wheeled military vehicle evolving in offroad conditions. Due to the rather wide range of missions UGVs may be involved in and to the computing cost of image processing, its computing resources have to be reprogrammable, of great power (real-time constraints), modular at the software level as well as at the hardware level and able to communicate with other systems. First, the paper details the mechanical, electronical and software design of the whole sensor. Then, we explain its functioning, the constraints due to its parallel processing architecture, the image processing algorithms that have been implemented for it and their current uses and performances. Finally, we describe experiments conducted on tracked and wheeled vehicles and conclude on the future development and use of this sensor for unmanned ground vehicles.
Our research deals with the design and experiment of a control architecture for an autonomous outdoor mobile robot which uses mainly vision for perception. In this case of a single robot, we have designed a hybrid architecture with an attention mechanism that allows dynamic selection of perception processes. Building on this work, we have developed an open multi-agent architecture, for standard multi-task operating system, using the C++ programming language and Posix threads. Our implementation features of efficient and fully generic messages between agents, automatic acknowledgement receipts and built-in synchronization capabilities. Knowledge is distributed among robots according to a collaborative scheme: every robot builds its own representation of the world and shares it with others. Pieces of information are exchanged when decisions have to be made. Experiments are to be led with two outdoor ActiveMedia Pioneer AT mobile robots. Distributed perception, using mainly vision but also ultrasound, will serve as proof of concept.
We discuss the research developed in our lab these past years, leading to autonomous robots evolving in non-cooperative, even hostile outdoor environments.
KEYWORDS: Visual process modeling, Sensors, Systems modeling, Machine vision, Visualization, Image processing, Computer architecture, Robotics, Control systems, Mobile robots
In this paper, we are interested in the design and the experiment of a control architecture for an autonomous outdoor mobile robot which mainly uses vision. We focus on the design of a mechanism that permits the dynamic selection and firing of perception processes. We propose a hybrid architecture that uses an attention mechanism which controls the robot environment awareness while managing the computational resources and allowing a fair reactivity. We describe its implementation and experimentation on a robot in an outdoor environment.
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