1,295 research outputs found

    Tier-Scalable Reconnaissance Missions For The Autonomous Exploration Of Planetary Bodies

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    A fundamentally new (scientific) reconnaissance mission concept, termed tier-scalable reconnaissance, for remote planetary (including Earth) atmospheric, surface and subsurface exploration recently has been devised that soon will replace the engineering and safety constrained mission designs of the past, allowing for optimal acquisition of geologic, paleohydrologic, paleoclimatic, and possible astrobiologic information of Venus, Mars, Europa, Ganymede, Titan, Enceladus, Triton, and other extraterrestrial targets. This paradigm is equally applicable to potentially hazardous or inaccessible operational areas on Earth such as those related to military or terrorist activities, or areas that have been exposed to biochemical agents, radiation, or natural disasters. Traditional missions have performed local, ground-level reconnaissance through rovers and immobile landers, or global mapping performed by an orbiter. The former is safety and engineering constrained, affording limited detailed reconnaissance of a single site at the expense of a regional understanding, while the latter returns immense datasets, often overlooking detailed information of local and regional significance

    Autonomous Navigation and Mapping using Monocular Low-Resolution Grayscale Vision

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    Vision has been a powerful tool for navigation of intelligent and man-made systems ever since the cybernetics revolution in the 1970s. There have been two basic approaches to the navigation of computer controlled systems: The self-contained bottom-up development of sensorimotor abilities, namely perception and mobility, and the top-down approach, namely artificial intelligence, reasoning and knowledge based methods. The three-fold goal of autonomous exploration, mapping and localization of a mobile robot however, needs to be developed within a single framework. An algorithm is proposed to answer the challenges of autonomous corridor navigation and mapping by a mobile robot equipped with a single forward-facing camera. Using a combination of corridor ceiling lights, visual homing, and entropy, the robot is able to perform straight line navigation down the center of an unknown corridor. Turning at the end of a corridor is accomplished using Jeffrey divergence and time-to-collision, while deflection from dead ends and blank walls uses a scalar entropy measure of the entire image. When combined, these metrics allow the robot to navigate in both textured and untextured environments. The robot can autonomously explore an unknown indoor environment, recovering from difficult situations like corners, blank walls, and initial heading toward a wall. While exploring, the algorithm constructs a Voronoi-based topo-geometric map with nodes representing distinctive places like doors, water fountains, and other corridors. Because the algorithm is based entirely upon low-resolution (32 x 24) grayscale images, processing occurs at over 1000 frames per second

    An Energy-Aware Algorithm for Large Scale Foraging Systems

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    International audienceThe foraging task is one of the canonical testbeds for cooperative robotics, in which a collection of coordinated robots have to find and transport one or more objects to one or more specific storage points. Swarm robotics has been widely considered in such situations, due to its strengths such as robustness, simplicity and scalability. Typical multi-robot foraging systems currently consider tens to hundreds of agents. This paper presents a new algorithm called Energy-aware Cooperative Switching Algorithm for Foraging (EC-SAF) that manages thousands of robots. We investigate therefore the scalability of EC-SAF algorithm and the parameters that can affect energy efficiency overtime. Results indicate that EC-SAF is scalable and effective in reducing swarm energy consumption compared to an energy-aware version of the reference well-known c-marking algorithm (Ec-marking)

    Odors: from chemical structures to gaseous plumes

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    We are immersed within an odorous sea of chemical currents that we parse into individual odors with complex structures. Odors have been posited as determined by the structural relation between the molecules that compose the chemical compounds and their interactions with the receptor site. But, naturally occurring smells are parsed from gaseous odor plumes. To give a comprehensive account of the nature of odors the chemosciences must account for these large distributed entities as well. We offer a focused review of what is known about the perception of odor plumes for olfactory navigation and tracking, which we then connect to what is known about the role odorants play as properties of the plume in determining odor identity with respect to odor quality. We end by motivating our central claim that more research needs to be conducted on the role that odorants play within the odor plume in determining odor identity

    Optical fibre local area networks

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