37 research outputs found

    Assistive trajectories for human-in-the-loop mobile robotic platforms

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    Autonomous and semi-autonomous smoothly interruptible trajectories are developed which are highly suitable for application in tele-operated mobile robots, operator on-board military mobile ground platforms, and other mobility assistance platforms. These trajectories will allow a navigational system to provide assistance to the operator in the loop, for purpose built robots or remotely operated platforms. This will allow the platform to function well beyond the line-of-sight of the operator, enabling remote operation inside a building, surveillance, or advanced observations whilst keeping the operator in a safe location. In addition, on-board operators can be assisted to navigate without collision when distracted, or under-fire, or when physically disabled by injury

    Convex Tours of Bounded Curvature

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    We consider the motion planning problem for a point constrained to move along a smooth closed convex path of bounded curvature. The workspace of the moving point is bounded by a convex polygon with m vertices, containing an obstacle in a form of a simple polygon with nn vertices. We present an O(m+n) time algorithm finding the path, going around the obstacle, whose curvature is the smallest possible.Comment: 11 pages, 5 figures, abstract presented at European Symposium on Algorithms 199

    Real Time Motion Generation for Mobile Robot

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    Approximate Kinodynamic Planning Using L2-Norm Dynamic Bounds

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    In this paper we address the issue of kinodynamic motion planning. Given a point that moves with bounded acceleration and velocity, we wish to find the time-optimal trajectory from a start state to a goal state (a state consists of both a position and a velocity). As finding exact optimal solutions to this problem seems very hard, we present a provably good approximation algorithm using the L2 norm to bound acceleration and velocity. Our results are an extension of the earlier work of Canny, Donald, Reif, and Xavier [1], who present similar results where the dynamics bounds can be examined in each dimension independently (they use the L&infin norm to bound acceleration and velocity)

    The Stochastic Motion Roadmap: A Sampling Framework for Planning with Markov Motion Uncertainty

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    Continuous-curvature paths for mobile robots

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    This paper discusses how to plan continuous-curvature paths for car-like wheeled mobile robots. The task is to generate a trajectory with upper-bounded curvature and curvature derivative. To solve this problem we use three path planning primitives, namely straight line segments, circular segments, and continuous-curvature turns (CC turns) in the path planning. We give a classification of the CC turns and we also describe the motion along different kinds of CC turns. We focus on giving computational effective formulae for real-time usage
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