Enabling Force Sensing during Ground Locomotion: A bio-inspired, multi-axis, composite force sensor using discrete pressure mapping.

TitleEnabling Force Sensing during Ground Locomotion: A bio-inspired, multi-axis, composite force sensor using discrete pressure mapping.
Publication TypeJournal Article
Year of Publication2014
AuthorsChuah, M. Yee, and S. Kim
JournalIEEE Sensors Journal
Volume14
Issue5
Start Page1693
Pagination1693 - 1703
Date Published05/2014
ISSN1530-437X
Accession Number14195346
Abstract

This paper presents a new force sensor design approach that maps the local sampling of pressureinside a composite polymeric footpad to forces in three axes, designed for running robots. Conventional multiaxis force sensors made of heavy metallic materials tend to be too bulky and heavy to be fitted in the feet of legged robots, and vulnerable to inertial noise upon high acceleration. To satisfy the requirements for high speed running, which include mitigating high impact forces, protecting thesensors from ground collision, and enhancing traction, these stiff sensors should be paired with additional layers of durable, soft materials; but this also degrades the integrity of the foot structure. The proposed foot sensor is manufactured as a monolithic, composite structure composed of an array of barometric pressure sensors completely embedded in a protective polyurethane rubber layer. Thiscomposite architecture allows the layers to provide compliance and traction for foot collision while the deformation and the sampled pressure distribution of the structure can be mapped into three axis forcemeasurement. Normal and shear forces can be measured upon contact with the ground, which causes the footpad to deform and change the readings of the individual pressure sensors in the array. A one-time training process using an artificial neural network is all that is necessary to relate the normal and shear forces with the multiaxis foot sensor output. The results show that the sensor can predict normalforces in the Z-axis up to 300 N with a root mean squared error of 0.66% and up to 80 N in the X- and Y-axis. The experiment results demonstrates a proof-of-concept for a lightweight, low cost, yet robust footpad sensor suitable for use in legged robots undergoing ground locomotion.

URLhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6714415
DOI10.1109/JSEN.2014.2299805
Original Publicationhttp://dspace.mit.edu/handle/1721.1/97549