Personal transportation is the act of transporting an individual by using a small, low-speed vehicle. It is a very hot research topic both in industry and academia. There are many different types of personal transportation vehicles, and wheelchairs are one of them. Autonomous driving is another very popular subject that is applicable to the personal transportation vehicles. Autonomous personal transportation vehicles are good examples of service robotics applications. In this study, conversion procedure of a conventional electric wheelchair into an autonomous personal transportation testbed and the application of some basic autonomous driving algorithms on the developed testbed are explained. In literature, there are several studies providing information on wheelchairs' autonomy but not deep information about the conversion itself. In this paper, the conversion process is investigated in detail, under two main sections. The first part is by-wire conversion, which allows the wheelchair to be controlled via computer commands. The second part includes the studies on sensors, computational system, and human interface. After making such modifications on wheelchair, fundamental algorithms required for autonomy, such as mapping and localization, are implemented successfully. The results are promising for the usage of the developed system as a testbed for examining new autonomous algorithms and evaluating the performance of the perceptional/computational components.
One of the most challenging tasks for autonomous robots is avoiding unexpected obstacles during their path following operation. Follow the gap method (FGM) is one of the most popular obstacle avoidance algorithms that recursively guides the robot to the goal state by considering the angle to the goal point and the distance to the closest obstacles. It selects the largest gap around the robot, where the gap angle is calculated by the vector to the midpoint of the largest gap. In this paper, a novel obstacle avoidance procedure is developed and applied to a real fully autonomous wheelchair. This proposed algorithm improves the FGM’s travel safety and brings a new solution to the obstacle avoidance task. In the proposed algorithm, the largest gap is selected based on gap width. Moreover, the avoidance angle (similar to the gap center angle of FGM) is calculated considering the locus of the equidistant points from obstacles that create obstacle circles. Monte Carlo simulations are used to test the proposed algorithm, and according to the results, the new procedure guides the robot to safer trajectories compared with classical FGM. The real experimental test results are in parallel to the simulations and show the real-time performance of the proposed approach.
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