Path Planning for drone using reinforcement learning simulation on Airsim

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I am looking for a freelancer who can assist me with path planning for a drone using reinforcement learning simulation on Microsoft AirSim. The project requires expertise in Deep Q-Learning as the preferred reinforcement learning algorithm.

Specific requirements for the drone path planning include navigating through an obstacle dense environment. The ideal freelancer should have experience in developing algorithms that can effectively navigate through such environments.

The preferred simulation tool for this project is Microsoft AirSim. The freelancer should have experience in working with AirSim and be able to utilize its features for the reinforcement learning simulation.

Key requirements:

- Proficiency in Deep Q-Learning

- Experience in path planning in obstacle dense environments

- Should have knowledge of YOLOv6 model for obstacle detection

- Integration of YOLO model with Airsim is must require

- Familiarity with Microsoft AirSim and its features for simulation

If you have the necessary skills and experience in these areas, please submit your proposal.

Video Processing Deep Learning

ID do Projeto: #37220370

Sobre o projeto

3 propostas Projeto remoto Ativo em 1 mês atrás

3 freelancers estão ofertando em média ₹9000 nesse trabalho

OlektraGroup

Hello, How are you? I have 6+ years experience in Video Processing and Deep Learning Mais

₹7000 INR in 15 dias
(7 Comentários)
5.2
amirrmusavifr

Hi, My name is Seyed Amirreza and I'm an experienced Python developer with the necessary skills to complete your project. I'm expert on Deep Reinforcement Learning and I already worked on model-based and model-free typ Mais

₹10000 INR em 1 dia
(5 Comentários)
3.1
kaliansh

I am currently working on deep reinforcement learning. And it's not necessary to go with deep q learning there r other approaches to create this project like A2C PPO algorithm etc. I have worked on bunch of environment Mais

₹10000 INR in 10 dias
(0 Comentários)
0.0