PL-CVIO: Point-Line Cooperative Visual-Inertial Odometry

Low-feature environments are one of the main Achilles' heels of geometric computer vision (CV) algorithms. In most human-built scenes often with low features, lines can be considered complements to points. In this paper, we present a multi-robot cooperative visual-inertial navigation system (VINS) using both point and line features. By utilizing the covariance intersection (CI) update within the multi-state constraint Kalman filter (MSCKF) framework, each robot exploits not only its own point and line measurements, but also constraints of common point and common line features observed by its neighbors. The line features are parameterized and updated by utilizing the Closest Point representation. The proposed algorithm is validated extensively in both Monte-Carlo simulations and a real-world dataset. The results show that the point-line cooperative visual-inertial odometry (PL-CVIO) outperforms the independent MSCKF and our previous work CVIO in both low-feature and rich-feature environments

Iterate to Innovate: How Firms Strategize Design Iteration to Navigate the Uneven Landscape in the Global Mobile Application Industry

This dissertation builds on the logic of opportunity and the institutional perspective to explore how firms iterate to innovate in the uneven landscape of the global digital marketplace. In such nascent industries, innovative firms could not rely on differential positioning or valuable resources to sustain advantage but must take actions of iterative search to capture fleeting opportunities. Specifically, I focus on the role of design iteration, through which firms engage in trial-and-error learning and create situation-specific knowledge. While this logic of opportunity has received a significant upsurge of interest from strategy and entrepreneurship scholars, it largely assumes a homogeneous institutional environment in which nascent industries are embedded. The assumption mostly holds because new industries emerge in advanced economies with similar institutions. However, as innovation becomes increasingly democratized on a global scale, firms operating in heterogeneous institutional contexts can simultaneously partake in nascent industries. It is therefore important for us to understand how firms should strategize design iteration to pursue distinctive flows of opportunities in/across various institutional contexts. Specifically, I develop three essays around this important inquiry in the context of the global mobile application industry. First, while extant research advises firms to continually iterate designs, I unveil the hidden dark side of design iteration using a difference-in-differences design based on mobile game apps that multihome on two platforms. In my second essay, I investigate how firms navigate varying levels of institutional uncertainty by strategizing their design iteration. I find that frequent design iterations enable firms to overcome high institutional uncertainty and capture opportunities to innovate new products. This study extends the logic of opportunity and a dynamic view of institutions. Third, I further explore how digital startups strategize iteration with rhythms to compete simultaneously across different institutional contexts. I find that while digital startups tend to iterate product designs with rhythms, they strategize such iteration rhythms differently to align with their international diversification conditions. My dissertation takes an initial but important step toward infusing opportunity logic with the institutional perspective and develops a rigorous, quantifiable, and generalizable understanding of how firms iterate to innovate in the global digital marketplace

On the LFM signal improvement by piecewise vibrational resonance using a new spectral amplification factor

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163797/1/sil2bf00702.pd

Classification of solutions of delay difference equations

In this paper we study the classification of solutions of delay difference equation{?2yn=Pnyn-myn=An???for???n=N-(m+1),…,N-1where An,n=N-(m+1),…,N-1 are given, m is a nonnegative integer