Enhanced Portable Navigation for Cycling Applications
Integrated Navigation System
Cycling Dead Reckoning
MetadataShow full item record
AbstractNavigation-capable portable devices have now blossomed into essential tools in a daily commute. With the evolution of motion sensors based on the advancements in Micro-Electric Mechanical Systems (MEMS), the number of consumer devices and applications that utilize MEMS-based sensors dramatically increased. The focus of this dissertation is about enhancing the navigation of portable devices for cycling navigation. Obtaining an accurate navigation solution continuously and seamlessly using portable devices in any orientation and without constraints is very challenging, especially during unavailability of absolute navigation information such as from the global navigation satellite system (GNSS). The main challenges are: (1) the device is not tethered to a moving platform, but rather moves in-run with respect to the moving platform and can be on the body of the cyclist and undergo any type of the motion dynamics; (2) the frame of the sensors can be in any orientation with respect to the frame of the bicycle and therefore, has time-varying orientation in each run; and (3) the error characteristics of the low-cost inertial sensors lead to growing position errors during the unavailability of absolute navigation information. In the far majority of prior research, techniques and aiding systems proposed to solve or mitigate problems are for driving and walking activities but not for cycling. The capability to obtain a meaningful navigation solution for cycling applications using a single portable device with low cost sensors is beneficial for both normal consumers and athletes. This dissertation proposes a novel cycling navigation solution using portable devices. The proposed solution includes the following novel modules: (1) pedaling detection to indicate pedaling phase used for the other proposed modules; (2) 3D misalignments to enable freely-used portable devices in any orientation; (3) Cycling Dead Reckoning (CDR) which depend on pedaling frequency to derive position and velocity; and (4) multi gear CDR (MG-CDR) which involves more than one CDR and an adaptive algorithm to adjust the parameters at different gear ratios. The performance of the proposed modules was validated on a large number of trajectories collected by different users, on different bicycles including both multi-gears and single-gear bicycles.
CitationChang, H. (2014). Enhanced Portable Navigation for Cycling Applications (Unpublished doctoral thesis). University of Calgary, Calgary, AB. doi:10.11575/PRISM/25902
University of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.