This paper proposes a novel network architecture based on content routing and dissemination techniques, expressly adapted for hybrid mobile and vehicular ad-hoc networks. Hybrid vehicular ad-hoc networks (VANETs) are a subclass of mobile ad-hoc networks (MANETs) where each node is a moving vehicle equipped with one or more communication devices, potentially having access to several different physical communication channels. This results in a partly decentralized, self-organizing mobile radio network with a fast changing topology. Applications designed for VANETs still require efficient mapping techniques to associate content to the host serving it, as well as centralized databases associating vehicles and mobile nodes to a persistent and unique identifier. They also assume that the content providers are located in the infrastructure, but nodes and vehicles can be equipped with sensors and as such produce information. This means that dissemination and retrieval algorithms have to take into account the distribution of the consumers, providers and forwarder all over the network.We propose an architecture based on Van Jacobson's Content Centric Networking, extended and modified to solve some of the issues related to content access and dissemination across hybrid VANETs. The implementation and simulation on a realistic platform are presented as well as an application to a real case scenario, demonstrating the efficiency of the approach.
The work presented in this paper belongs to the realm of robotics and computer vision. The problem we seek to solve is the accomplishment of robotics tasks using visual features provided by a special sensor, mounted on a robot end effector. This sensor consists of two laser stripes fixed rigidly to a camera, projecting planar light on the scene. First, we briefly describe the classical visual servoing approach. We then generalize this approach to the case of our special sensor hy considering its interaction with respect to a sphere. This interaction permits us to establish a kinematics relation between the sensor and the scene. Finally, both in simulation and in our experimental cell, the results are presented. They concern the positioning task with respect to a sphere, and show the robustness and the stability of the control scheme.
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