A SIMULTANEOUS PATH PLANNING AND POSITIONING BASED ON ARTIFICIAL DISTRIBUTION OF LANDMARKS IN A GNSS DENIED ENVIRONMENT

In recent years, exploration operations by autonomous robots are expanding into unknown environments on Earth, under the sea, or even on other planets. This paper proposes the idea of Concurrent Path Planning and Positioning (CPPAP) using artificially distributed landmarks, while no GNSS signal is available. The method encompasses an observability-based direction search algorithm for path planning in parallel with Simultaneous Localization and Mapping (SLAM) for localization. Most of the path planning methods utilize offline algorithms; however, the proposed method determines the robot’s direction of motion in real-time, concurrently with the positioning tasks by the inclusion of the system observability, related to the features’ distribution. Same as in all feature-based SLAMs, features play an important role in determination of the most observable direction, and hence the direction of the robot’s motion. Moreover, the effectiveness of the distribution of the features and their pattern in the proposed method is investigated. To evaluate the efficiency and accuracy of the CPPAP, outcomes are compared with an existing random SLAM.