Date of Graduation
Statler College of Engineering and Mineral Resources
Mechanical and Aerospace Engineering
Exploration with mobile robots is a well known field of research, but current solutions cannot be directly applied for tethered robots. In some applications, tethers may be very important to provide power or allow communication with the robot. This thesis presents an exploration algorithm that guarantees complete exploration of arbitrary environments within the length constraint of the tether, while keeping the tether tangle-free at all times. While a generalized algorithm that can be used with several exploration strategies is also proposed, the presented implementation uses a modified frontier-based exploration approach, where the robot chooses its next goal in the frontier between explored and unexplored regions of the environment. The main modification from standard frontier-based method is the use of a cost function to sort multiple goals in one iteration and pick the cheapest one to go to, minimizing global path length in the process. The cost is calculated in terms of path length with tether constraints accounted for. The basic idea of the algorithm is to keep an estimate of the tether configuration, including length and homotopy, and decide the next robot path based on the length difference between the current tether length and the shortest tether length at the next goal position. The length difference is then used to determine whether it is safe for the robot to take the shortest path to the goal, or whether the robot has to take a different path to the goal in the way that would put the tether back into the most optimal configuration. The maximum length difference that would still guarantee global tangle-free paths has been shown to be the circumference of the smallest expected obstacle in the environment. The presented algorithm is provable correct and was tested and evaluated using both simulations and real-world experiments. Navigation of a planar robot is done with the aid of a Simultaneous Localization and Mapping (SLAM) system, with the data being provided by the on-board LiDAR scanner. The results from conducted experiments have demonstrated that the proposed algorithm results in the total path length increase of anywhere from 30% up to to 80% compared to untethered frontier-based approach, with the exact percentage increase dependent on the complexity of the environment. It is also approximately 6 times shorter than the total path length in a conservative approach of backtracking to the base to avoid tangling.
Shapovalov, Danylo, "Exploration of Unknown Environments Using a Tethered Mobile Robot" (2020). Graduate Theses, Dissertations, and Problem Reports. 7895.