Training a simulated drone with deep reinforcement learning

This report details the comprehensive planning, execution, and evaluation of a solodeveloped project in the field of artificial intelligence (AI) and software engineering.
The project, focused on implementing a drone capable of autonomous navigation and delivery, follows the Agile Scrum methodology for project management. The report covers various aspects, including risk management, iterative development processes, and the application of the Soft Actor-Critic (SAC) algorithm for AI training.
A key aspect of the report is the detailed description of the SAC algorithm, which outlines the mathematical principles of this algorithm in an understandable way.
The development lifecycle is outlined through a series of sprints, each encompassing planning, review, and retrospective meetings. The report underscores the importance of risk management, categorizing and addressing potential challenges throughout the project.
Detailed insights into the project’s structure, from backlogs to sprints, provide a transparent view of the iterative development process. The challenges faced, such as lack of experience with AI and Unreal Engine, are mitigated through proactive measures, including research and adaptation.
The long-term plan, presented in a Gantt chart, highlights key milestones, phases, and features. Primary and secondary features, along with epics and milestones, are meticulously defined, allowing for a clear understanding of project progress.
The report concludes with a thorough retrospective, highlighting successes, areas for improvement, and personal reflections. Key achievements include overcoming the hyperparameter problem and implementing the SAC algorithm to control the drone.