KEYWORDS: Sensors, Reconnaissance, Human-machine interfaces, Computer architecture, Cameras, Signal processing, Surveillance, Control systems, Personal digital assistants, Data processing
In this paper, we present our research on the control of a mobile robot for indoor reconnaissance missions. Based on previous work concerning our robot control architecture HARPIC, we have developed a man machine interface and software components that allow a human operator to control a robot at different levels of autonomy. This work aims at studying how a robot could be helpful in indoor
reconnaissance and surveillance missions in hostile environment. In
such missions, since a soldier faces many threats and must protect himself while looking around and holding his weapon, he cannot devote his attention to the teleoperation of the robot. Moreover, robots are not yet able to conduct complex missions in a fully autonomous mode. Thus, in a pragmatic way, we have built a software that allows dynamic swapping between control modes (manual, safeguarded and behavior-based) while automatically performing map building and localization of the robot. It also includes surveillance functions like movement detection and is designed for
multirobot extensions. We first describe the design of our agent-based robot control architecture and discuss the various ways to control and interact with a robot. The main modules and functionalities implementing those ideas in our architecture are
detailed. More precisely, we show how we combine manual controls,
obstacle avoidance, wall and corridor following, way point and planned travelling. Some experiments on a Pioneer robot equipped with various sensors are presented. Finally, we suggest some promising directions for the development of robots and user interfaces for hostile environment and discuss our planned future improvements.
In a previous presentation at AeroSense 2002, we described a methodology to assess the results of image processing algorithms for ill-structured road detection and tracking. In this paper, we present our first application of this methodology on sixedge detectors and a database counting about 20,000 images.
Our evaluation approach is based on the use of video image sequences, ground truth - reference results established by human experts - and assessment metrics which measure the quality of the image processing
results. We need a quantitative, comparative and repetitive evaluation of many algorithms in order to direct future developments.
The main scope of this paper consists in presenting the lessons learned from applying our methodology. More precisely, we describe the assessment metrics, the algorithms and the database. Then we describe how we manage to extract the qualities and weaknesses of each algorithm and to establish a global scoring. The insight we gain
for the definition of assessment metrics is also presented.
Finally, we suggest some promising directions for the development of road tracking algorithms and complementarities that must be sought after. To conclude, we describe future improvements for the database constitution, the assessment tools and the overall methodology.
In this paper, we present a methodology to assess the results of image processing algorithms for unstructured road edges detection. We aim at performing a quantitative, comparative and repetitive evaluation of numerous algorithms in order to direct our future developments in navigation algorithms for military unmanned vehicles. The main scope of this paper is the constitution of this database and the definition of the assessment metrics.
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.
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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