Computer Vision based SLAM Algorithm

As part of my master's studies, I undertook a significant project focusing on the implementation and evaluation of a cutting-edge computer vision SLAM (Simultaneous Localization and Mapping) algorithm. This algorithm leverages the capabilities of 360-degree cameras to enhance the precision and efficiency of mapping and localization in various environments.

The primary goal of my dissertation was to implement a novel vision-based SLAM algorithm and to rigorously test its performance under different conditions. Through comprehensive analysis and experimentation, I aimed to:

- Identify the operational strengths of the algorithm and the scenarios in which it excels.

- Determine the limitations and challenges faced by the algorithm in real-world applications.

- Establish the conditions necessary for the algorithm to perform optimally.

My dissertation further explored the entrepreneurial impact of this novel technology by looking into the market size and trends of specific industries that may be affected by this technology.