TY - GEN
T1 - Indoor mapping and localization for a smart wheelchair using measurements of ambient magnetic fields
AU - Trezza, Anthony T.
AU - Virani, Nurali N.
AU - Wolkowicz, Kelilah L.
AU - Moore, Jason Z.
AU - Brennan, Sean N.
N1 - Publisher Copyright:
© 2015 by ASME.
PY - 2015
Y1 - 2015
N2 - Freedom of mobility is a crucial aspect of our daily lives. Consequently, engineering solutions for mobility, includ- ing smart wheelchairs, are becoming increasingly important for those with disabilities. However, the lack of a reliable solution for indoor localization has affected the pace of research in this direction. GPS signals cannot be measured indoors and envi- ronment modifications for wheelchair localization can be expen- sive and intrusive. This research explores the feasibility of us- ing ambient magnetic fields for indoor localization by exploit- ing the spatial non-uniformity due to ferromagnetic objects in ordinary working environments. A non-parametric density esti- mation technique was developed to build magnetic field maps. This approach is compared to an existing regression technique. Two different approximate kinematic models for the wheelchair are presented and implemented in a particle-filtering frame- work. Finally, the efficacy of these mapping techniques and motion models, including and excluding odometry information, are compared via tracking experiments conducted with a smart wheelchair.
AB - Freedom of mobility is a crucial aspect of our daily lives. Consequently, engineering solutions for mobility, includ- ing smart wheelchairs, are becoming increasingly important for those with disabilities. However, the lack of a reliable solution for indoor localization has affected the pace of research in this direction. GPS signals cannot be measured indoors and envi- ronment modifications for wheelchair localization can be expen- sive and intrusive. This research explores the feasibility of us- ing ambient magnetic fields for indoor localization by exploit- ing the spatial non-uniformity due to ferromagnetic objects in ordinary working environments. A non-parametric density esti- mation technique was developed to build magnetic field maps. This approach is compared to an existing regression technique. Two different approximate kinematic models for the wheelchair are presented and implemented in a particle-filtering frame- work. Finally, the efficacy of these mapping techniques and motion models, including and excluding odometry information, are compared via tracking experiments conducted with a smart wheelchair.
UR - http://www.scopus.com/inward/record.url?scp=84973513720&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84973513720&partnerID=8YFLogxK
U2 - 10.1115/DSCC2015-9915
DO - 10.1115/DSCC2015-9915
M3 - Conference contribution
AN - SCOPUS:84973513720
T3 - ASME 2015 Dynamic Systems and Control Conference, DSCC 2015
BT - Multiagent Network Systems; Natural Gas and Heat Exchangers; Path Planning and Motion Control; Powertrain Systems; Rehab Robotics; Robot Manipulators; Rollover Prevention (AVS); Sensors and Actuators; Time Delay Systems; Tracking Control Systems; Uncertain Systems and Robustness; Unmanned, Ground and Surface Robotics; Vehicle Dynamics Control; Vibration and Control of Smart Structures/Mech Systems; Vibration Issues in Mechanical Systems
PB - American Society of Mechanical Engineers
T2 - ASME 2015 Dynamic Systems and Control Conference, DSCC 2015
Y2 - 28 October 2015 through 30 October 2015
ER -