Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Patents
Publisher : 2018.
Source : 2018.
Campus : Amritapuri
School : School of Engineering
Department : Electronics and Communication
Year : 2018
Abstract : Electric wheelchairs are now more intelligent due to the use of algorithms that provide assisted driving. Typically, the user steers the electric wheelchairs with conventional analog joysticks. This implies the need for an appropriate methodology to map the position of the joystick handle in a Cartesian coordinate system to the wheelchair motor velocities. This mapping of joystick positions to individual wheel speed can be done in an infinite number of combinations. However it is this mapping that will determine the response behavior of the wheelchair to the user manual control. This paper describes the implementation of several joystick mappings in an intelligent wheelchair prototype. Experiments were performed in a realistic simulator using 25 users with distinct driving abilities. The users had 6 different joystick control mapping methods and for each user the usability and preference order was measured. The results achieved enable to conclude that a more direct mapping between the joystick’s coordinates and the wheelchair behavior is preferred by the majority of the users.
Cite this Research Publication : Rajesh Kannan Megalingam, “Multi-Mode Control (Manual, Fixed and Self-driving) ROS Based Wheelchair ”, 2018.