Design and implementation of a new speed planner for semiautonomous systems

Abstract

In this paper, a new speed planning method is developed for semiautonomous systems by improving ourprevious fuzzy logic-based approach. In this proposed method, an extended risk factor is calculated on top of the classicalrisk factor, using environmental factors and the user’s speed reference. We obtain safer speed values in critical scenarioswith this new extended risk factor definition. Another improvement comes from the design of the semiautonomousarchitecture. Instead of the fully autonomous solution of the previous work, we calculate the final speed reference bycombining 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 adifferential drive wheelchair platform controlled via head movements. The results of the tests show that the proposedfuzzy-based semiautonomous speed planner using an extended risk factor provides safer transportation than its previousvariant.