Showing 341 - 360 results of 1,315 for search '"motion planning"', query time: 0.71s Refine Results
  1. 341

    A Motion Planning Method for Omnidirectional Mobile Robot Based on the Anisotropic Characteristics by Chuntao Leng, Qixin Cao, Yanwen Huang

    Published 2008-11-01
    “…A more suitable motion planning method for an omni-directional mobile robot (OMR), an improved APF method (iAPF), is proposed in this paper by introducing the revolving factor into the artificial potential field (APF). …”
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    Real-time Motion Planning in Unknown Environments for Legged Robotic Planetary Exploration by Albee, Keenan Eugene Sumner, Cabrales Hernandez, Alejandro, Jia-Richards, Oliver, Terán Espinoza, Antonio

    Published 2021
    “…If deviation occurs, long communication delays often result in rover downtime and subsequent lost time for scientific exploration. Onboard robotic motion planning that is fast and accounts for obstacles and robot kinematics is one key piece of the autonomy pipeline required to bring more meaningful autonomy to planetary exploration. …”
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    Coordinated motion planning: Reconfiguring a swarm of labeled robots with bounded stretch by Demaine, Erik

    Published 2021
    “…We present a number of breakthroughs for coordinated motion planning, in which the objective is to reconfigure a swarm of labeled convex objects by a combination of parallel, continuous, collision-free translations into a given target arrangement. …”
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    Gadgets and Gizmos: A Formal Model of Simulation in the Gadget Framework for Motion Planning by Hendrickson, Dylan

    Published 2022
    “…Recent work has developed a theory of motion-planning gadgets, which are a useful tool for proving hardness for a variety of problems that can be thought of in terms of an agent navigating a dynamic environment. …”
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    Online Information-Aware Motion Planning with Model Improvement for Uncertain Mobile Robotics by Albee, Keenan Eugene Sumner

    Published 2022
    “…Accounting for these uncertainties when performing robotic motion planning provides a richer approximation of reality, unlocking tools such as robustness or chance-constrained safety guarantees, improving motion planning optimality, and more. …”
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