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Guiding Vector Fields for Robot Motion Control
Using a designed vector field to guide robots to follow a given geometric desired path has found a range of practical applications, such as underwater pipeline inspection, warehouse navigation, and highway traffic monitoring. It is thus in great need to build a rigorous theory to guide practical implementations with formal guarantees. It is even so when multiple robots are required to follow predefined desired paths or maneuver on surfaces and coordinate their motions to efficiently accomplish repetitive and laborious tasks. The book introduces guiding vector fields on Euclidean spaces and Riemannian manifolds for single-robot and multi-robot path-following and motion coordination, provides ...
Shock Absorbers Or Transmitters? The Role of Foreign Banks During COVID-19
This paper studies whether bank ownership influenced lending behavior during the COVID-19 shock. It finds that, similar to previous episodes of financial distress, foreign banks appear to have played a shock-transmitting role, as there was a sharp slowdown in lending by foreign banks’ affiliates relative to domestic banks. However, given the uniqueness of the COVID-19 shock and the impact of lockdowns on economic activity, foreign banks were found to lend at a higher rate than domestic banks once the stringency of mobility restrictions is accounted for, with their lending portfolio concentrated more in the corporate sector. Results also suggest that the difference in lending rates between foreign and domestic banks could be explained by the heterogeneous effects of policy measures in response to the pandemic. In jurisdictions with more stringent mobility restrictions, policy interventions actually encouraged higher lending by foreign banks. These findings suggest that foreign bank presence may have acted as a shock absorber in jurisdictions where economic activity was most affected by the pandemic.
Policy Options for Supporting and Restructuring Firms Hit by the COVID-19 Crisis
This paper presents principles that could guide the design of more targeted policy support and facilitate the restructuring of firms adversely impacted by the COVID-19 pandemic. To this end, the paper takes stock of vulnerabilities and risks in the enterprise sector and assesses countries’ preparedness to handle a large-scale restructuring of businesses. Crisis preparedness of insolvency systems is measured according to a newly designed indicator that includes five dimensions of the insolvency and restructuring regime (out-of-court restructuring, hybrid restructuring, reorganization, liquidation, and the institutional framework). Vulnerabilities tend to be more pronounced in jurisdictions with shortcomings in crisis preparedness, and those countries need to step up efforts to improve their insolvency systems.
Robot Operating System (ROS)
This second volume is a continuation of the successful first volume of this Springer book, and as well as addressing broader topics it puts a particular focus on unmanned aerial vehicles (UAVs) with Robot Operating System (ROS). Consisting of three types of chapters: tutorials, cases studies, and research papers, it provides comprehensive additional material on ROS and the aspects of developing robotics systems, algorithms, frameworks, and applications with ROS. ROS is being increasingly integrated in almost all kinds of robots and is becoming the de-facto standard for developing applications and systems for robotics. Although the research community is actively developing applications with R...
RoboCup 2018: Robot World Cup XXII
This book includes the post-conference proceedings of the 22nd RoboCup International Symposium, held in Montreal, QC, Canada, in June 2018. The 32 full revised papers and 11 papers from the winning teams presented were carefully reviewed and selected from 51 submissions. This book highlights the approaches of champion teams from the competitions and documents the proceedings of the 22nd annual RoboCup International Symposium. Due to the complex research challenges set by the RoboCup initiative, the RoboCup International Symposium offers a unique perspective for exploring scientific and engineering principles underlying advanced robotic and AI systems.
Handle with Care: Regulatory Easing in Times of COVID-19
The policy response to the COVID-19 shock included regulatory easing across many jurisdictions to facilitate the flow of credit to the economy and mitigate a further ampli-fication of the shock through tighter financial conditions. Using an intraday event study,this paper examines how stock prices—a key driver in financial conditions—reacted to regulatory easing announcements in a sample of 18 advanced economies and 8 emerging markets. The paper finds that overall, regulatory easing announcements contributed to looser financial conditions, but effects varied across sectors and tools. Financial regulatory easing led to lower valuations for financial sector stocks, and higher valuations for non-financial sector stocks, particularly for industries that are more dependent on bank financing. Furthermore, valuations declined and financial conditions tightened following announcements related to easier bank capital regulation while equity valuation rose and financial conditions loosened after those about liquidity regulation. Effects from non-regulatory financial measures appear to be generally more muted.
Effects of Macroprudential Policy: Evidence from Over 6,000 Estimates
This paper builds a novel database on the effects of macroprudential policy drawing from 58 empirical studies, comprising over 6,000 results on a wide range of instruments and outcome variables. It encompasses information on statistical significance, standardized magnitudes, and other characteristics of the estimates. Using meta-analysis techniques, the paper estimates average effects to find i) statistically significant effects on credit, but with considerable heterogeneity across instruments; ii) weaker and more imprecise effects on house prices; iii) quantitatively stronger effects in emerging markets and among studies using micro-level data; and iii) statistically significant evidence of leakages and spillovers. Other findings include relatively stronger impacts for tightening than loosening actions and negative effects on economic activity in the near term.
Macroeconomic Developments and Prospects in Low-Income Developing Countries
"This paper is the fourth in a series that examines macroeconomic developments and prospects in Low Income Developing Countries (LIDCs). LIDCs are Fund member countries where gross national income (GNI) per capita lies below a threshold level and where external financial linkages and socioeconomic indicators have not lifted them into emerging market status. There are 59 countries in the LIDC grouping, accounting for about one-fifth of the world’s population and 4 percent of global output. The paper examines macroeconomic trends across LIDCs in recent years, contrasting key features of the current situation with the period prior to the 2014 decline in commodity prices. Particular attention is given to the evolution of fiscal positions and public debt levels, including detailed analysis of the drivers of debt accumulation and the current severity of debt vulnerabilities. The analysis is grounded in, and draws on, the analysis and databases used to compile the World Economic Outlook: this report drills down into the WEO database to look in detail at the experience of LIDCs."
People’s Republic of China
Selected Issues
How to Assess Country Risk
The IMF’s Vulnerability Exercise (VE) is a cross-country exercise that identifies country-specific near-term macroeconomic risks. As a key element of the Fund’s broader risk architecture, the VE is a bottom-up, multi-sectoral approach to risk assessments for all IMF member countries. The VE modeling toolkit is regularly updated in response to global economic developments and the latest modeling innovations. The new generation of VE models presented here leverages machine-learning algorithms. The models can better capture interactions between different parts of the economy and non-linear relationships that are not well measured in ”normal times.” The performance of machine-learning-based models is evaluated against more conventional models in a horse-race format. The paper also presents direct, transparent methods for communicating model results.
