Conditional Task and Motion Planning through an Effort-based Approach

This paper proposes a preliminary work on a Conditional Task and Motion Planning algorithm able to find a plan that minimizes robot efforts while solving assigned tasks. Unlike most of the existing approaches that replan a path only when it becomes unfeasible (e.g., no collision-free paths exist), the proposed algorithm takes into consideration a replanning procedure whenever an effort-saving is possible. The effort is here considered as the execution time, but it is extensible to the robot energy consumption. The computed plan is both conditional and dynamically adaptable to the unexpected environmental changes. Based on the theoretical analysis of the algorithm, authors expect their proposal to be complete and scalable. In progress experiments aim to prove this investigation

Detecting the Unexpected via Image Resynthesis

Classical semantic segmentation methods, including the recent deep learning ones, assume that all classes observed at test time have been seen during training. In this paper, we tackle the more realistic scenario where unexpected objects of unknown classes can appear at test time. The main trends in this area either leverage the notion of prediction uncertainty to flag the regions with low confidence as unknown, or rely on autoencoders and highlight poorly-decoded regions. Having observed that, in both cases, the detected regions typically do not correspond to unexpected objects, in this paper, we introduce a drastically different strategy: It relies on the intuition that the network will produce spurious labels in regions depicting unexpected objects. Therefore, resynthesizing the image from the resulting semantic map will yield significant appearance differences with respect to the input image. In other words, we translate the problem of detecting unknown classes to one of identifying poorly-resynthesized image regions. We show that this outperforms both uncertainty- and autoencoder-based methods

The Critical Incident Technique

{Excerpt} Organizations are often challenged to identify and resolve workplace problems. The Critical Incident technique gives them a starting point and a process for advancing organizational development through learning experiences. It helps them study “what people do” in various situations. One might think there are no answers to the following questions: How fast can you think on your feet? How do you react in the face of the unexpected? How can you prepare if you cannot predict? And yet, there are. Evidently, some behaviors contribute to the successor failure of individuals—and organizations—in specific situations. And so, responses to the unforeseen lie in identifying before the fact events or circumstances, or series of them, that are outside the range of ordinary human experiences. The questions posed earlier are as old as mankind; but our ability to address them owes largely to the relatively recent work of John Flanagan. These days critical incidents can be harvested to provide a rich, personal perspective of life that facilitates understanding of the issues and obstacles people face every now and then and illuminates avenues for improvement (or replication if outcomes are effective)—avenues that may not be apparent through purely quantitative methods of data collection. This should matter to high-performance organizations

Logic, self-awareness and self-improvement: The metacognitive loop and the problem of brittleness

This essay describes a general approach to building perturbation-tolerant autonomous systems, based on the conviction that artificial agents should be able notice when something is amiss, assess the anomaly, and guide a solution into place. We call this basic strategy of self-guided learning the metacognitive loop; it involves the system monitoring, reasoning about, and, when necessary, altering its own decision-making components. In this essay, we (a) argue that equipping agents with a metacognitive loop can help to overcome the brittleness problem, (b) detail the metacognitive loop and its relation to our ongoing work on time-sensitive commonsense reasoning, (c) describe specific, implemented systems whose perturbation tolerance was improved by adding a metacognitive loop, and (d) outline both short-term and long-term research agendas

Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder

In this paper, we present a hierarchical path planning framework called SG-RL (subgoal graphs-reinforcement learning), to plan rational paths for agents maneuvering in continuous and uncertain environments. By "rational", we mean (1) efficient path planning to eliminate first-move lags; (2) collision-free and smooth for agents with kinematic constraints satisfied. SG-RL works in a two-level manner. At the first level, SG-RL uses a geometric path-planning method, i.e., Simple Subgoal Graphs (SSG), to efficiently find optimal abstract paths, also called subgoal sequences. At the second level, SG-RL uses an RL method, i.e., Least-Squares Policy Iteration (LSPI), to learn near-optimal motion-planning policies which can generate kinematically feasible and collision-free trajectories between adjacent subgoals. The first advantage of the proposed method is that SSG can solve the limitations of sparse reward and local minima trap for RL agents; thus, LSPI can be used to generate paths in complex environments. The second advantage is that, when the environment changes slightly (i.e., unexpected obstacles appearing), SG-RL does not need to reconstruct subgoal graphs and replan subgoal sequences using SSG, since LSPI can deal with uncertainties by exploiting its generalization ability to handle changes in environments. Simulation experiments in representative scenarios demonstrate that, compared with existing methods, SG-RL can work well on large-scale maps with relatively low action-switching frequencies and shorter path lengths, and SG-RL can deal with small changes in environments. We further demonstrate that the design of reward functions and the types of training environments are important factors for learning feasible policies.Comment: 20 page

Organizational culture, leadership style and effectiveness: A case study of middle eastern construction clients

During the last few decades, organizational effectiveness has received a great deal of attention in many industrial sectors. As a result, a variety of models have been formulated which measure organizational performance. In the construction industry, two factors have subsequently captured the imagination and interest of researchers and practitioners alike: the culture of the organization and the leadership style of project managers. This focus places a requirement upon construction organizations to recognize and understand their organizational culture, and equally, to clearly communicate it to their employees as part of their capitalist drive of constantly improving performance, productivity and profit. Traditional ways of conducting construction business require a sound understanding of the technical and managerial demands of executing projects, which in turn, places an increased emphasis upon the management and leadership competencies of individual project managers. The purpose of the research is to explore the relationship between organizational culture, authentic leadership style and effectiveness within the context of a case study investigation centred on Middle Eastern construction clients and their project managers. The outcomes of the investigation, which include the presentation of an explanatory model, indicate that organizational culture is directly and positively related to performance and effectiveness, while project managers' leadership style has an indirect relationship to effectiveness. A strong organizational culture is therefore deemed critical to organizational performance

Institutional obstacles to doing business : region-by-region results from a worldwide survey of the private sector

Case studies and anecdotal evidence have suggested that uncertainty about policies, laws, and regulations has hampered development of the private sector in many developing countries. The authors present results from a new cross-country survey that provides comparable data on local investors'problem in dealing with the state. The survey was conducted in 69 countries and covers more than 3,600 entrepreneurs. The questionnaire asked 25 questions about investors'perceptions about such issues as the predictability of laws and policies, the reliability of the judiciary, corruption in bureaucracies, and security of property rights. It also asked about general obstacles to doing business and the quality of state-delivered services. The authors discuss their methodology and present many findings. Among them: a) In less developed countries the majority of entrepreneurs constantly fear policy surprises and unexpected changes in rules that can seriously affect their business. Entrepreneurs in Asia have the most trust in government announcements of policy changes and changes in rules; entrepreneurs in the Commonwealth of Independent States are the most cynical about new announcements; and half of businessmen surveyed in Latin America and Central and Eastern Europe do not believe government announcements. b) Entrepreneurs worldwide feel that the cost of doing business is substantially increased by theft and crime and in many developing countries the business community feels that authorities do not adequately guarantee their personal safety and do not reliably enforce their property rights. c) Unreliable judiciaries are perceived as major problems in many developing countries. This applies in particular to the Commonwealth of Independent States and to Latin American countries. d) Entrepreneurs in industrial countries perceived the greatest obstacles to doing business to be tax regulations and high taxes, labor regulations, safety or environmental regulations, financing, regulations for starting new business and operations, and general uncertainty about the costs of regulation. e) Entrepreneurs in South Asia and Southeast Asia ranked the top obstacles to doing business as high taxes and tax regulations, inadequate infrastructure, inflation, labor regulations, and regulations for starting new businesses and operations. f) In the Middle East and North Africa, entrepreneurs considered lack of infrastructure the chief obstacle to doing business, followed by corruption, high taxes and tax regulations, and financing. g) In Central and Eastern Europe, high taxes and tax regulations were the only regulation-related obstacle ranked high, followed by financing, corruption, and inflation. h) The worst obstacles in Latin America were considered to be corruption and inadequate infrastructure, followed by crime and theft, problems with finance, and high taxes and tax regulation. i) In Sub-Saharan Africa the biggest problems were corruption, tax regulations and high taxes, inadequate infrastructure, inflation, crime and theft, and financing.Environmental Economics&Policies,Decentralization,Public Health Promotion,Health Monitoring&Evaluation,Enterprise Development&Reform,National Governance,Environmental Economics&Policies,Health Monitoring&Evaluation,Private Participation in Infrastructure,Small Scale Enterprise

Managing financial constraints: Undercapitalization and underwriting capacity in spanish fire insurance

Reinsurance is a vital financial device for enhancing underwriting capacity, ceding risks and mitigating financial distress. By supplying financial resources and services, reinsurance can facilitate growth and expansion in the insurance business. Focusing on the insurance sector in the emerging Spanish economy and using a novel dataset on fire insurance companies, this paper examines the role of fire insurance in the capital formation, the importance of reinsurance as a vehicle for expanding the country’s domestic underwriting capacity, and how the capital import impacted on the balance of payment, from the introduction of the first comprehensive legislation regarding insurance in 1908 to the outbreak of the Civil War in 1936. Considering the situation of undercapitalization, the singularities of the insurance market, and the changes in regulatory schemes, we find that foreign reinsurance became a key financial vehicle for increasing the underwriting capacity in Spain. We also show the struggle for an emerging market to find ways to keep balance of current accounts and raise capital when the financial infrastructure is underdeveloped. The diffusion of reinsurance networks from the core of industrial Western countries towards emerging economies was one of the mechanisms for financial modernization on a global scale

A robust extended H-infinity filtering approach to multi-robot cooperative localization in dynamic indoor environments

Multi-robot cooperative localization serves as an essential task for a team of mobile robots to work within an unknown environment. Based on the real-time laser scanning data interaction, a robust approach is proposed to obtain optimal multi-robot relative observations using the Metric-based Iterative Closest Point (MbICP) algorithm, which makes it possible to utilize the surrounding environment information directly instead of placing a localization-mark on the robots. To meet the demand of dealing with the inherent non-linearities existing in the multi-robot kinematic models and the relative observations, a robust extended H∞ filtering (REHF) approach is developed for the multi-robot cooperative localization system, which could handle non-Gaussian process and measurement noises with respect to robot navigation in unknown dynamic scenes. Compared with the conventional multi-robot localization system using extended Kalman filtering (EKF) approach, the proposed filtering algorithm is capable of providing superior performance in a dynamic indoor environment with outlier disturbances. Both numerical experiments and experiments conducted for the Pioneer3-DX robots show that the proposed localization scheme is effective in improving both the accuracy and reliability of the performance within a complex environment.This work was supported inpart by the National Natural Science Foundation of China under grants 61075094, 61035005 and 61134009