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Contribution to Book
Intelligent and autonomous wheelchair design: Demo abstract
SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems
  • Karan Daryani, San Jose State University
  • Aakash Chitroda, San Jose State University
  • Aquib Mulani, San Jose State University
  • Venkatesh Tanniru, San Jose State University
  • Kaikai Liu, San Jose State University
Publication Date
11-16-2020
Document Type
Conference Proceeding
DOI
10.1145/3384419.3430409
Abstract

Many people have difficulty walking, and the percentage of people with this challenge increases with age. The "mobility challenge,"which we address in this project, centers on one's ability to independently move through the world. Enabling individuals to maintain their independence of mobility has significant social importance for society as a whole. While research in sensing and autonomous technology has made great strides in recent years, affordable fully autonomous systems are still a distant goal, primarily because of a lack of sensing accuracy and robustness based on off-the-shelf low-cost sensors. Self-driving vehicles being tested by companies rely heavily on expensive 3D LiDAR to locate themselves on the detailed maps they need to get around, and to identify things like pedestrians and other vehicles. In this project, we investigate an efficient sensing and perception hardware and software system design for autonomous and intelligent wheelchairs. The goal is to develop an experimental testbed with multi-modal sensors, computing systems, control and mobility systems. This affordable testbed will be a full-fledged modular platform to test and deploy latest deep learning-based algorithm without expensive hardware components.

Citation Information
Karan Daryani, Aakash Chitroda, Aquib Mulani, Venkatesh Tanniru, et al.. "Intelligent and autonomous wheelchair design: Demo abstract" SenSys 2020 - Proceedings of the 2020 18th ACM Conference on Embedded Networked Sensor Systems (2020) p. 625 - 626
Available at: http://works.bepress.com/kaikai-liu/37/