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Showing 1 to 7 of 7 for “"Informative Path Planning"”.

  1. Learning for informative path planning

    … intensive Monte- Carlo simulations in informative path planning. This will enable us to decrease the uncertainty of the weather estimates more than current methods by enabling the evaluation of many more candidate paths given the same amount of resources. The learning method and the …

    mit Repository record for Learning for informative path planning (opens in a new tab)

  2. Learning a Spatial Field in Minimum Time with a Team of Robots

    We study an informative path planning problem where the goal is to minimize the time required to learn a spatial field. Specifically, our goal is to ensure that the mean square error between the learned and actual fields is below a predefined value. We study three versions of the problem. In the …

    vt Repository record for Learning a Spatial Field in Minimum Time with a Team of Robots (opens in a new tab)

  3. Active Perception for Inertial-Aided Systems

    … characterize IMU biases. This thesis proposes Informative Path Planning (IPP) frameworks that actively maximize information gain in inertial-aided perception tasks of extrinsic calibration, localization and mapping. Firstly, we propose an algorithm to generate continuous and differentiable …

    uts Repository record for Active Perception for Inertial-Aided Systems (opens in a new tab)

  4. Deep reinforcement learning for adaptive monitarizacion and patrolling of water resources with unmanned surface vehicles

    … and lakes have been outlined: on one hand, informative path planning, consisting of obtaining the best possible model, and on the other hand, informative patrolling, consisting of a persistent monitoring of the environment. Both problems have been addressed from the single-agent and …

    sevilla Repository record for Deep reinforcement learning for adaptive monitarizacion and patrolling of water resources with unmanned surface vehicles (opens in a new tab)

  5. Robotic Search Planning In Large Environments with Limited Computational Resources and Unreliable Communications

    … To accomplish this task, robots must plan paths through the region of interest that maximize the effectiveness of the sensors they carry. Receding horizon path planning is a popular approach to addressing the computationally expensive task of planning long paths because it allows robotic …

    vt Repository record for Robotic Search Planning In Large Environments with Limited Computational Resources and Unreliable Communications (opens in a new tab)

  6. INFORMATION BASED ADAPTIVE PATH PLANNING AND SAMPLING FOR ENVIRONMENT MONITORING

    … processes. We first explain the two adaptive planning algorithms for estimating scalar environmental fields with bounds on the mission time. These algorithms adapt the path during the mission based on the recently collected information. We use Sparse Gaussian Processes for field estimation and …

    nus Repository record for INFORMATION BASED ADAPTIVE PATH PLANNING AND SAMPLING FOR ENVIRONMENT MONITORING (opens in a new tab)

  7. Risk-Aware Human-In-The-Loop Multi-Robot Path Planning for Lost Person Search and Rescue

    We introduce a framework that would enable using autonomous aerial vehicles in search and rescue scenarios associated with missing person incidents to assist human searchers. We formulate a lost person behavior model and a human searcher model informed by data collected from past search missions. …

    vt Repository record for Risk-Aware Human-In-The-Loop Multi-Robot Path Planning for Lost Person Search and Rescue (opens in a new tab)