Powered-wheelchair transducers and systems are presented that provided more control, reduced veer on slopes, and improved energy conservation, while reducing effort. They are especially significant for people with movement disorders who lack sufficient hand-grasp and release ability or sufficient targeting skill to use joysticks. Design/methodologies/approach Laboratory test rigs were created to test the proportional switches and to teach potential users. Then a rolling road was created and trials were conducted with the road and real situations. Caster angle measurement was selected to provide feedback to minimize drift away from a chosen course and an electronic solution was created to match driver control to caster steering position. A case study is described as an example. Findings Results and advantages are presented from changing from using a set of digital-switches on a wheelchair to a set of new variable-switches and then adding a sensor system to prevent veer on slopes. The systems have been tested for more than 18 months and shown to assist powered-wheelchair users with poor targeting skills. Research limitations The research used typical wheelchairs with caster wheels but systems could easily be used on other wheelchairs. Practical implication Simple input-devices are presented that isolate gross motor function and are tolerant to involuntary movements (proportional-switches). A sensor system is presented that assists users in steering across sloping or uneven ground. Originality/Value The proportional-switches and sensors were shown to reduce veer and to provide more control over turn and forward speed and turn radius while reducing frustration and improving energy conservation. The simple and affordable systems could be created and attached to many standard powered-wheelchairs in many organisations.. The powered-wheelchair users became more independent when using the new systems.
A simple expert system is described that helps wheelchair users to drive their wheelchairs. The expert system takes data in from sensors and a joystick, identifies obstacles and then recommends a safe route. Wheelchair users were timed while driving around a variety of routes and using a joystick controlling their wheelchair via the simple expert system. Ultrasonic sensors are used to detect the obstacles. The simple expert system performed better than other recently published systems. In more difficult situations, wheelchair drivers did better when there was help from a sensor system. Wheelchair users completed routes with the sensors and expert system and results are compared with the same users driving without any assistance. The new systems show a significant improvement.
E ffects of motion lag on the capability of a teleope rate d mobile-robot operator are investigated. Lags can occur through communication delays as telc-operated mobile robots work at a distance or becau se of a lack of parallel computing powe r as robots are enhanced with add itional systems. This work conce ntrates on time lag in a tele-operated mobile robot syste m and inve stigates when a mobile robot operator might be gin to pe rceive a lag in the movement of a mobile robot. A thre shold of pe rmissible lag is established for mobile robot ope rators that re lates to the maximum time lag before an ope rator notice d a lag.
The integration of proportional switches for human-computer interaction and sensors with veer correction systems are presented. The transducers and sensors improve control, assist wheelchair drivers and reduced wheelchair veer, especially on slopes. The systems also reduce effort. The proportional switches are particularly useful for disabled people who do not have enough skill to use a joystick, or who lack sufficient hand-grasp and release ability, or who have movement disorders. The new systems were tested using laboratory test rigs. The test rigs were reused later to teach human users. A rolling road was then built to test the systems before user trials were undertaken. The angle of the wheelchair casters provided feedback and that feedback was used to reduce drift. A new electronic system matched the caster angles to the driver input. A case study is described. Results are presented, and they suggest there are advantages to using variable rather than digital or binary switches. The veer correction system can assist when a user is traversing a slope. The transducers and systems have been tested at Chailey heritage and proved to be useful in assisting poweredwheelchair users. The proportional switches isolate the gross motor functions and filter out uncontrolled movement. The sensor system helps users to steer on uneven or sloping ground. The transducers also provide more control during turning and can reduce the turn radius as well as lowering frustration and conserving energy.
Simple and affordable systems are described to assist wheelchair users in steering their wheelchairs across sloping ground. The systems can be attached to many standard powered wheelchairs. Wheelchairs often steer by having two swivelling caster wheels but problems with this configuration occur when a wheelchair is driven along sloping ground because the casters can swivel in the direction of the slope. Gravity then causes the wheelchair to start an unwanted turn or ‘veer’ and the chair goes in an unintended direction. This situation is exacerbated for switch users, as switches cannot provide fine control to trim and compensate. Early experiments demonstrated that calibrating wheelchair controllers for straight‐line balance and optimising motor‐compensation did not solve this problem. Caster angle was selected to provide feedback to the wheelchair controllers. At the point when veer is first detected, a wheelchair has already begun to alter course and the job of the correction system is to minimise this drift from the desired course. A rolling road was created as an assessment tool and trials with both the test bed and in real situations were conducted to evaluate the new systems. The small swivel detector that was created could be successfully attached to caster swivel bearings. The new system was successful, robust and was not affected by changeable parameters. Although primarily intended for switch users, the methods can be applied to users with proportional controls.
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.
The research presented in this paper creates an intelligent system that collects powered wheelchair users' driving session data. The intelligent system is based on a Python programming platform. A program is created that will collect data for future analysis. The collected data considers driving session details, the ability of a driver to operate a wheelchair, and the type of input devices used to operate a powered wheelchair. Data is collected on a Raspberry Pi microcomputer and is sent after each session via email. Data is placed in the body of the emails, in an attached file and saved on microcomputer memory. Modifications to the system is made to meet confidentiality and privacy concerns of potential users. Data will be used for future analysis and will be considered as a training data set to teach an intelligent system to predict future path patterns for different wheelchair users. In addition, data will be used to analyze the ability of a user to drive a wheelchair, and monitor users' development from one session to another, compare the progress of various users with similar disabilities and identify the most appropriate input device for each user and path.
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