Titlebook: Intelligent Unmanned Ground Vehicles; Autonomous Navigatio Martial H. Hebert,Charles Thorpe,Anthony Stentz Book 1997 Springer Science+Busin

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0893-3405 n the course of the DARPA Unmanned Ground Vehicle(UGV) project. The goal of this work was to equip off-road vehicleswith computer-controlled, unmanned driving capabilities. The bookdescribes contributions in the area of mobility for UGVs including:tools for assembling complex autonomous mobility sys

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Book 1997se of the DARPA Unmanned Ground Vehicle(UGV) project. The goal of this work was to equip off-road vehicleswith computer-controlled, unmanned driving capabilities. The bookdescribes contributions in the area of mobility for UGVs including:tools for assembling complex autonomous mobility systems; on-r

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A Behavior-based Architecture for Mobile Navigation,eleoperation. Because of the disparate nature of the raw sensor data and internal representations used by these subsystems, combining them into one coherent system which includes all their capabilities has proven to be very difficult.

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SAUSAGES: Between Planning and Action,or important events, etc. A system that can execute a complex mission cannot simply be the sum of its perceptual modalities; there needs to be a “plan” which uses high level knowledge about goals and intentions to direct the behaviors of the low level perception and actuation modules.

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A Navigation System for Goal Acquisition in Unknown Environments,w, by combining the SMARTY system for obstacle detection and avoidance described in Chapter 6 with the D* planning system described in Chapter 11, we are able to conduct long-range autonomous missions with dynamic map building and path planning.

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SMARTY: Point-Based Range Processing for Autonomous Driving,fied at long range with the added requirement that simple strategies such as elevation thresholds do not work because of the complexity of the terrain. Without making any distinction, we will refer to regions of the environment in which the vehicle is not allowed to drive as obstacle regions or as untraversable regions.

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RANGER: Feedforward Control Approach to Autonomous Navigation,em called RANGER, an acronym for Real-time Autonomous Navigator with a Geometric Engine, which implements those ideas. This chapter describes the “geometric engine” part of RANGER: the state space model, and the associated control algorithms.

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Sensor Fusion For Autonomous Navigation Using Neural Networks,nomous tasks in a given environment. But current systems have significant limitations. A single CCD camera is sufficient for road following, but not for extended road driving tasks; a laser range finder is sufficient for obstacle avoidance, but not for cross country navigation in “interesting” terrains.

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STRIPE: Low-Bandwidth and High-Latency Teleoperation,sensors. Teleoperation is needed in situations in which the terrain is deemed too difficult for autonomous operation or when the operator wishes to retain control over the path followed by the vehicle.