Performance evaluation of mobile stereonet for real time navigation in autonomous mobile robots

This research focuses on the performance evaluation of mobile stereonet for real-time navigation in mobile robots. The use of mobile stereonet for depth estimation and path planning has become increasingly important in the field of robotics. The research is conducting by implementing the mobile stereonet algorithm for real time navigation on a Raspberry Pi 4 and integrating it with a stereo camera to capture live video frames. The objective of this research is to evaluate the effectiveness of mobile stereonet in navigating mobile robots in different real time environments. The study will include the development of a mobile stereonet-based depth estimation and path planning system and its evaluation through simulations and experiments. The performance of the system will be evaluated based on various metrics, such as accuracy, efficiency, and robustness. The results of this study will provide insights into the potential applications of mobile stereonet in the field of robotics and contribute to the development of better navigation system for mobile robots using stereo vision technology. Implemented real time map generation using mobile stereonet is available on Github.