Some rule based techniques are presented that can assist powered wheelchair drivers. The expert system decides on the direction and speed of their wheelchair. The system tends to avoid obstacles while having a tendency to turn and head in towards a desired destination. This is achieved by producing a new target angle as an extra input. Other inputs are from sensors and a joystick. Directions are recommended and mixed with user inputs from the joystick representing desired direction and desired speed. The rule-based system decides on an angle to turn the powered wheelchair and suggest it. Inputs from the joystick and sensors are mixed with the suggested angle from the Rule Based Expert System. A modified direction for the wheelchair is produced. The whole system helps disabled wheelchair users to drive their powered wheelchairs.

Research is presented that uses the Preference Ranking Organization METHod for Enrichment of Evaluations II (PROMETHEE II) to determine a direction for a powered wheelchair. This is the first time this sort of decision making has been employed for this sort of use. A wheelchair user proposes a preferred speed and direction, and a decision-maker recommends a safe bearing. The two directions are combined so that the wheelchair safely avoids obstacles. Ultrasonic sensors and joysticks provide the inputs and the final direction is a combination of the preferred bearing and a route that safely avoids obstacles. The systematic decision-making process assists a powered wheelchair user with safely steering their wheelchair. Sensitivity analysis explores the potential directions and an appropriate direction is chosen that gives a robust solution. A user can override suggestions from the PROMETHEE II system by holding their joystick in a fixed place.

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The research presented in this paper describes a new architecture for controlling powered wheelchairs. A Raspberry Pi microcomputer is considered to assist in controlling direction. A Raspberry Pi is introduced between user input switches and powered wheelchair motors to create an intelligent Human Machine Interface (HCI). An electronic circuit is designed that consists of an ultrasonic sensor array and a set of control relays. The sensors delivered information about obstructions in the surrounding environment of the wheelchair. Python programming language was used to create a program that digitized the user switches output and assessed information provided by the ultrasonic sensor array. The program was installed on a Raspberry Pi and the Raspberry Pi controlled power delivered to the motors. Tests were conducted and results showed that the new system successfully assisted a wheelchair user in avoiding obstacles. The new architecture can be used to intelligently interface any input device or sensor system to powered wheelchair.

This paper presents a new technique for controlling powered wheelchairs. A Raspberry Pi microcomputer is used to assist in controlling direction. A Raspberry Pi is inserted between user input switches and powered wheelchair motors to create a more intelligent Human Machine Interface (HMI). An electronic circuit is created that consists of an ultrasonic sensor array and a set of control relays. The sensors provided information about obstacles surrounding the wheelchair. Python programming language was used to create a code that digitized the output from the user switches and assessed information provided by the ultrasonic sensor array. The code was loaded onto a Raspberry Pi and the Raspberry Pi controlled voltages supplied to the motors. Tests were conducted and results showed that the new system can successfully assist a wheelchair user in avoiding obstacles. The system can be used as an intelligent interface between any input device or sensor system and wheelchair motors.