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Visar resultat 1 - 5 av 7 uppsatser som matchar ovanstående sökkriterier.

  1. 1. Autonomous UAV Path Planning using RSS signals in Search and Rescue Operations

    Master-uppsats, Linköpings universitet/Reglerteknik

    Författare :Axel Anhammer; Hugo Lundeberg; [2022]
    Nyckelord :UAV; DQN; Deep Q Network; particle filter; point mass filter; MDP; POMDP; Markov decision process; partially observable Markov decision process;

    Sammanfattning : Unmanned aerial vehicles (UAVs) have emerged as a promising technology in search and rescue operations (SAR). UAVs have the ability to provide more timely localization, thus decreasing the crucial duration of SAR operations. LÄS MER

  3. 2. Risk-aware Autonomous Driving Using POMDPs and Responsibility-Sensitive Safety

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Caroline Skoglund; [2021]
    Nyckelord :Computer Science - Robotics; Autonomous driving; partially observable Markov decision process; motion planning under uncertainty; risk estimation;

    Sammanfattning : Autonomous vehicles promise to play an important role aiming at increased efficiency and safety in road transportation. Although we have seen several examples of autonomous vehicles out on the road over the past years, how to ensure the safety of autonomous vehicle in the uncertain and dynamic environment is still a challenging problem. LÄS MER

  4. 3. Belief-aided Robust Control for Remote Electrical Tilt Optimization

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Jack Jönsson; [2021]
    Nyckelord :Mobile Network Optimization; Remote Electrical Tilt; Robust Control; Reinforcement Learning; Partially Observable Markov Decision Process; Belief State Estimation; Bayesian Neural Network; Optimering av Mobilnätverk; Fjärrstyrning av Elektrisk Lutning; Robust Reglering; Delvis Observerbar Markovprocess; Tillståndsestimering; Bayesiskt Neuralt Nätverk;

    Sammanfattning : Remote Electrical Tilt (RET) is a method for configuring antenna downtilt in base stations to optimize mobile network performance. Reinforcement Learning (RL) is an approach to automating the process by letting an agent learn an optimal control strategy and adapt to the dynamic environment. LÄS MER

  5. 4. Deep Reinforcement Learning for Autonomous Highway Driving Scenario

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Neil Pradhan; [2021]
    Nyckelord :Deep reinforcement learning; Highway driving scenario; Tactical decision making; fuel reduction; high-level decision making; autonomous driving; Partially Observable Markov Decision Process POMDP .; Lärande om djupförstärkning; motorvägsscenario; taktiskt beslutsfattande; bränslereduktion; beslut på hög nivå; autonom körning; Partially Observable Markov Decision Process POMDP ;

    Sammanfattning : We present an autonomous driving agent on a simulated highway driving scenario with vehicles such as cars and trucks moving with stochastically variable velocity profiles. The focus of the simulated environment is to test tactical decision making in highway driving scenarios. LÄS MER

  7. 5. A Partially Observable Markov Decision Process for Breast Cancer Screening

    Master-uppsats, Linköpings universitet/Statistik och maskininlärning

    Författare :Joshua Hudson; [2019]
    Nyckelord :POMDP; Markov Decision Process; Breast Cancer; Screening; Operations Research;

    Sammanfattning : In the US, breast cancer is one of the most common forms of cancer and the most lethal. There are many decisions that must be made by the doctor and/or the patient when dealing with a potential breast cancer. LÄS MER