Akademik Veri Yönetim Sistemi
TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES, cilt.26, sa.2, ss.693-706, 2018 (SCI-Expanded)
In this paper, a new speed planning method is developed for semiautonomous systems by improving our previous fuzzy logic-based approach. In this proposed method, an extended risk factor is calculated on top of the classical risk factor, using environmental factors and the user's speed reference. We obtain safer speed values in critical scenarios with this new extended risk factor definition. Another improvement comes from the design of the semiautonomous architecture. Instead of the fully autonomous solution of the previous work, we calculate the final speed reference by combining the risk factor-based speed value and user's speed reference, which provides a semiautonomous solution. The developed fuzzy logic-based semiautonomous speed planner was tested in simulations and real environments on a differential drive wheelchair platform controlled via head movements. The results of the tests show that the proposed fuzzy-based semiautonomous speed planner using an extended risk factor provides safer transportation than its previous variant.