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.
- 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.
ID проекта: #37220370