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Titlebook: Robotics Research; The 14th Internation Cédric Pradalier,Roland Siegwart,Gerhard Hirzinger Conference proceedings 2011 Springer Berlin Heid

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Design and Development of an Optimal-Control-Based Framework for Trajectory Planning, Threat Assessmion to this threat. This approach minimizes controller intervention while ensuring that the vehicle does not depart from a navigable corridor of travel. Simulation and experimental results are presented here to demonstrate the framework’s ability to incorporate configurable intervention laws while sharing control with a human driver.
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Stable Dynamic Walking over Rough Terraine-of-freedom biped with hip actuation but pointed stilt-like feet. The technique is, however, very general and can be applied to higher degree-of-freedom robots over arbitrary terrain and other impulsive mechanical systems.
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Design and Development of an Optimal-Control-Based Framework for Trajectory Planning, Threat Assessmonomous control of passenger vehicles in hazard avoidance scenarios. This framework allows for multiple actuation modes, diverse trajectory-planning objectives, and varying levels of autonomy. A model predictive controller iteratively plans a best-case vehicle trajectory through a navigable corridor
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Autonomy through SLAM for an Underwater Robotcesses. This autonomy is used to carry out undersea target reacquisition missions that would otherwise be impossible with a low-cost platform. The AUV requires only simple sensors and operates without navigation equipment such as Doppler Velocity Log, inertial navigation or acoustic beacons. Demonst
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Sensing and Control on the Spheresphere for attitude estimation, control and scene structure estimation. This paper proposes the sphere as a unifying concept, not just for cameras, but for sensor fusion, estimation and control.We review and summarize relevant work in these areas and illustrate this with relevant simulation examples
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Stable Dynamic Walking over Rough Terrainuch a system is an underactuated “dynamic walking” biped robot walking over rough terrain. The proposed technique is to compute a transverse linearization about the desired motion: a linear impulsive system which locally represents dynamics about a target trajectory. This system is then exponentiall
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