An Experimental Testbed for Optimized Wheelchair Control
Principal Investigator/s: Dan Ding, PhD
Co-Investigator/s: Songfeng Guo, PhD; Garrett Grindle
Funding Source: University of Pittsburgh Medical Center CMRF grant
2005-2006
Electric-powered wheelchairs (EPWs) provide functional mobility for people with both lower and upper extremity impairments. Advances have been made in the design of electric powered wheelchairs over the past 20 years, yet the control algorithms and general performance of these wheelchairs have not been improved significantly since the early 1980’s. In the robotics field, advanced sensing and control technologies are frequently used for enhanced performance and intelligence. However, most EPWs today still use the simple proportional-integral (PI) controller for velocity control, which does not perform well when subjected to disturbances, uncertainties, and load variation. Electric-powered wheelchair driving could become safer, more effective in a broader array of environments, and functional for more people with the application of emerging sensing and control technologies. To test and evaluate the advanced sensing and control technologies and investigate their applications into electric powered wheelchairs, the following specific aims are proposed: Aim1. To develop an electric power wheelchair base as a testbed consisting of a network of sensors and data logging function. Aim 2. To validate and determine the effectiveness of the previous developed adaptive robust control algorithm by comparing its performance with traditional velocity control algorithms using the wheelchair testbed. Aim 3. To investigate the feasibility of detecting wheel slippage through different sensor combinations for further traction management of EPWs under unfavorable road conditions. Aim 2 and Aim 3 are only two example applications where the wheelchair testbed can be used to transform ideas into implementation. Additionally, the wheelchair testbed can help characterize wheelchair behaviors for problem diagnosis, develop and validate novel algorithms to enhance wheelchair intelligence, and evaluate different solutions to optimize wheelchair performance. For each specific aim, the development process includes both circuit or algorithm design and bench tests. This study affects EPW users in a most personal and immediate manner. Information gathered may change the way EPW are designed, and how individuals are fitted for their EPWs. This study represents an important step towards creating the next generation of EPW controls.