Domain-Specific Challenges in Autonomy

[rczyba][✓ rczyba, 2025-06-29]

Autonomous technologies and robotics are redefining possibilities, improving efficiency and safety across sectors. Advanced applications such as self-driving vehicles, crop and harvesting robots rely on precise GNSS/GPS positioning and require centimeter-level accuracy to function properly. As the domain of autonomous applications expands, the ability to use reliable, real-time GNSS/GPS correction services becomes not only useful, but essential. A significant challenge is how to navigate autonomously by unmanned vehicles in environments with limited or no access to localization data. Autonomous navigation without GNSS is a complex and rapidly evolving technology area that has the potential to revolutionize many industries and applications. Key technologies and methods for navigation that lack GNSS information include inertial navigation systems (INS), vision-based localization, Lidar, and indoor localization systems. Promising results are also provided by SLAM technology, which is used to simultaneously determine the robot's position (location) and build a map of the environment in which it moves. Each of the technologies mentioned above has its advantages and disadvantages, but none of them provides a complete overview of the current state of the surrounding world. Although autonomous navigation technology without GNSS has many advantages, it also encounters challenges. These include, among others, difficulties in accurate measurement in an unknown or changing environment and problems with sensor calibration, which can lead to navigation errors.