By Topic

Worst-cases prediction by human in lifting objects with a power assist robot system: Effectiveness of a novel control strategy to improve the system performances in worst-cases

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
S. M. Mizanoor Rahman ; Dept. of Mechanical Engineering, Faculty of Engineering, Mie University, Tsu, 514-8507, Japan ; Ryojun Ikeura ; Hideki Sawai

We constructed a 1 DOF power assist robot for lifting objects of different sizes. We hypothesized that human's perception of weight due to inertia might be different from the perceived weight due to gravity when lifting an object with the power assist robot. In this article, we particularly looked at human's load force features, weight perception and object's motions in lifting objects with the power assist robot in worst-cases situations. We called it a worst-case when the human faced any uncertainty, sudden change in work environment, doubt or unusual situation prior to or at the moment of lifting. We considered two potential worst-cases. In the first case, subject's vision was obstructed by a screen prior to lifting the object with the robot. In the second case, the object was tilted at the moment of lifting. We then critically analyzed human's load forces, weight perception and object's motions for two cases separately. We then applied a novel control technique to two cases separately to reduce the excessive load forces and to improve the system performances. We also compared the findings derived in worst-cases to that derived in usual cases (i.e., when vision was not obstructed and objects were not tilted). Finally, we proposed to use the human features and the control technique to develop human-friendly power assist robots for lifting heavy objects in industries such as manufacturing, mining, transport, construction etc.

Published in:

Biomedical Robotics and Biomechatronics (BioRob), 2010 3rd IEEE RAS and EMBS International Conference on

Date of Conference:

26-29 Sept. 2010